Anybody who has spent any significant time on the internet will be familiar with the following scenario…
You’ve searched for a product, let’s say running shoes. Maybe you decided to make a purchase, or perhaps you were just looking for information. But now, adverts for various running shoes are following you to every corner of the web, from news sites to social media platforms.
This can be an unsettling experience, with many people flocking to digital detoxes or attempting to reclaim their data after being ‘creeped out’ by ads chasing them around the internet. As we enter this new decade, how can brands better balance connected experiences, data collection and personalisation against the perception they’re crossing the line into invasive behaviour?
Consumer catch 22
I’ve worked in tech for over 13 years but, perhaps surprisingly, I don’t have an Alexa or Google Home as I worry about privacy issues. I’m uneasy at the idea of an Oyster card being able to track my whereabouts and I left Facebook about three years ago.
So as much as I understand how data collection works and have a healthy distrust when handing over my information, the irony is that I am prepared to embrace it if it makes my life significantly easier.
And I’m not alone in embracing this contradiction. A recent consumer survey from Boxever found that 60 percent preferred offers that are targeted to where they are and what they are doing, but 62 percent said that they do not want retailers tracking their location.
A large-scale global study from Microsoft called The Consumer Data Value Exchange, highlighted a similar paradox and Gartner research has shown that the more data points marketers use to personalise communication, the more consumers see that communication as invasive.
So, what can brands do to break out of this catch-22 scenario?
Transparency and timing are key
According to Accenture, 66 percent of consumers want companies to earn customer trust by being more transparent about how their information is being used. Other recent research shows
it’s possible to achieve a balance between personalisation and privacy – outlining that 64 percent of consumers are happy with retailers taking their purchase history as long as it led to more bespoke offers.
A Forrester report predicts that the industry will “say goodbye to third-party data and hello to zero-party data – data customers own and willingly provide to brands”.
But brands must be careful to be useful at exactly the right time. For example, the easyJet app offers tailored promotions to customers at the time of travel through mobile vouchering. They’re adding value to the customer journey, both literally and figuratively.
Customers aren’t faced with a deluge of marketing material at all times. Instead, it’s ideally timed, relevant and therefore more likely to be viewed as non-invasive.
Don’t be over-familiar and treat people as individuals
When retail giant Target identified 25 products that, when analysed together, allowed them to assign shoppers with a ‘pregnancy prediction’ score, they unsurprisingly received lots of negative publicity.
“With the pregnancy products, though, we learned that some women react badly,” a Target executive said. But they learned their lesson – not to be too familiar – and started using a different approach.
“We started mixing in all these ads for things we knew pregnant women would never buy, so the baby ads looked random,” the exec added.
“We’d put an ad for a lawn mower next to diapers. We’d put a coupon for wine glasses next to infant clothes. That way, it looked like all the products were chosen by chance. And we found out that as long as a pregnant woman thinks she hasn’t been spied on, she’ll use the coupons.”
This proves it’s more about the positioning than the actual offers themselves. People like to be treated as individuals, not lumped into a broad category such as ‘pregnant women’. A perfect example of this preference for individualisation was the ‘Share a Coke’ campaign run by Coca-Cola.
Not only was it a clever way to capture customer data – people really wanted their names on bottles of Coke – it actually increased sales for the first time in years.
The golden age of personalisation
As brands become more experienced in the relative cost and reward of personalisation, they will get smarter about how to engage their customer base in a mutually beneficial manner.
Rather than just adding to the noise, brands will see returns from creating relevant offers that cultivate non-invasive relationships. When executed well, personalisation can drive impulse purchases, lead to increased revenue, and fewer returns. But if poorly implemented, brands risk irreparable damage to their already cautious customer base and being thought of as ‘creepy’.
For brands, the golden age of personalisation will come when the experience is so frictionless and positive, that customers don’t notice its persuasive influence anymore.
As we dive head-first into the holiday season, we can expect to see a familiar set of stories about the changing face of the retail industry. Headlines will no doubt focus on consumers’ increasing reliance on online shopping and how it is compounding the tight margins and challenging trade environment that retailers with physical locations must battle. This is, in fact, a disruption which has been taking place since the dot-com bubble – and nearly as long as the term ‘disruption’ has been in popular business parlance.
A more recent consequence of this disruption has been the emergence of omnichannel retail, in which the Customer Experience online and in-store is brought together and purchasing journeys can move seamlessly between online store-fronts, social media, targeted advertising, mobile apps, and physical retail locations.
As a way of converting a greater portion of product interest into product sales, omnichannel has emerged as a key defensive measure against tightening margins and falling footfall. One Harvard Business Review study found that omnichannel shoppers spend four percent more during each store visit and 10 percent more online than shoppers who only use one or the other channel.
Even more bullish analysis from the ICSC found that operating across multiple channels leads to an average follow-on spend of $167 online for every $100 spent in-store.
The business upsides of an omnichannel strategy, like the business pressures driving its adoption, are well known and broadly accepted. Much less, however, has been said about the technological change which lies beneath this evolution. Traditional retailers are increasingly moving essential IT infrastructure to the cloud, tempted first of all by the lure of being able to scale costs with demand and in line with often fluctuating revenues.
Combining these reduced overheads with increased revenue, however, means not just replacing traditional IT infrastructure with public cloud solutions on a like-for-like basis, but taking the opportunity to optimise the huge data sets that retail generates. Unifying duplicated data, rationalising database structures, and opening lines of communication between silos of information means that the product on a shop floor, the product’s page on an ecommerce site, and the product photo displayed in an online advert can all, from the perspective of the business’s IT systems, be understood as the same item.
While this transformation in how data is managed – together with a boost in available processing power – is bringing different retail channels into alignment, it also establishes the foundations upon which emerging technologies can be implemented.
If Step One for a retail business is converging its data, and Step Two is using that data to converge its physical and digital channels, retailers are increasingly discovering the benefits of a Step Three in which it is made more valuable with AI. As cloud computing becomes prevalent, we will see the addition of AI bring unexpected benefits to how personalised shopping can be, how environmentally friendly it can be, what kinds of experience it can give – and a retail sector which can disrupt even as it is being disrupted.
To take personalisation as an example: this is already a familiar experience for all of us from shopping online. In its simplest form, retailers promoting items on the basis of ‘customers also shopped for’ find significant potential for upselling, as an online shopping basket gives so much more detail about what a customer needs than where they are in a store does.
Data sourced from the context of physical retail stores can also be collected, analysed, and applied in ways which are analogous to this. From how many customers visit a location, to the route they take through the shop, to how they interact with different product lines, there is a rich source of information in traditional retail which is only now – thanks to AI-based analysis – becoming available.
This unstructured, organic information is fundamentally more difficult to make use of than the natively digital information of online shopping baskets and website interaction. As retailers on-board these capabilities, information on how factors from outside the business affect shopping behaviours also becomes available.
Weather or sporting events, for example, or broad cultural trends which pertain to specific segments of the buying audience, or cultural factors which are specific to a store’s location all change what people buy and when. Businesses which have invested in the technology needed for omnichannel retail find themselves in a position to collect this data and go beyond the personalisation which is prevalent in online shopping. Rather than focusing on correlation – ‘people who buy x also buy y’ – AI-powered analytics is opening up the potential for causation-based shopping predictions – ‘people buy y because of x’.
Looking beyond the immediate task of upselling, it’s easy to see other ways in which this level of insight might be applied. Anticipating when someone will need a product and shipping it to them just in time, connecting people with locally-stocked or manufactured products to minimise transport carbon emissions, and offering specific product configurations on an individual basis are just a few examples.
People with an interest in retail marketing or disruptive technology, or both, will be aware that the retail industry has for some time been engaging in consumer-facing demonstrations of this kind of technology – such as Westfield’s AI-powered Trending Store.
Beneath such one-offs, however, there is something more fundamental happening: as retail businesses upgrade their ability to gather, analyse, and apply data, traditional shopping as a whole will begin to behave more like its online counterpart in how it responds to the customer. We might therefore look at retail’s emerging data-driven potential also as its post-disruption reality – and other industries might want to look to retail to see what’s in their own future. How will access to rich contextual insights into a person’s needs and requirements affect sectors like finance, healthcare, or transport?
Well, retail has been in the thick of disruption for longer than anything else; that should be where we look to find the next steps.
With days to go to the annual seasonal sales extravaganza, including Black Friday, the holiday season is well and truly upon us.
Like many other consumers, I often start readying my gift shopping lists in the autumn. From my many conversations with Monetate clients, I understand that the challenge for retailers to stand out amongst competitors is tougher than ever.
It’s a crowded market, and brands must build strong foundations to nurture that purchase relationship, looking beyond deep discounts and a one-size-fits-all approach, to create a personalised shopping experience.
For 63 percent of consumers, personalisation from brands and retailers is now an expectation, however two-thirds of marketers are failing to invest in the appropriate technology to deliver this.
Smart personalisation strategies can be the key change factor as brands push to stand out and drive conversions. As Brexit looms, so too does the financial uncertainty facing consumers. Brands and retailers must rise above this and focus their efforts on cementing sustainable and long-lasting relationships that will in turn withstand what is expected to be a nervy and unsteady holiday season.
Our latest Ecommerce Benchmarkreport noted that ecommerce conversion rates dropped by seven percent in Q1 – a trend likely to have been driven by Brexit.
So how can marketers overcome the barriers that can often stand in the way when creating an optimised Customer Experience? As retailers strive to be best-placed to meet demand ahead of the busy ecommerce period, the following factors should be key considerations.
When it comes to personalisation, there is no blanket approach; recognising that every customer behaves differently with unique expectations is crucial.
Distilling audiences into groups by location, device, or demographic is an effective way to begin. These insights can work in tandem with machine learning and will enable brands to use real-time models to identify what works best for each individual. The use of data should continue to improve a shoppers’ personal experience as insights inform the how, the where, and the when to inform the best tactic for interaction with each potential customer.
Get to the heart of the customer
It’s easy to become buried in customer data, which is where segmentation and analytics tools are incredibly handy; providing instant insights into your customer behaviour, using everything from simple attributes such as device type and geography to more complex attributes such as product categories viewed and brands purchased.
Actionable customer data is the key to success when implementing a one-to-one personalisation programme, which drives higher conversion rates, increases average order value (AOV), and increases the quality of CX.
The more data available, the more effective and tailored the personalisation will be, but you can start small to reap value from the offset. From there, brands and retailers will be able to easily scale any personalisation efforts as they grow in data maturity and continue to get to know their customers.
Follow the data signals
When marketers think of multi-screening, they often see it as a new challenge or obstacle, but the truth is that we live in a multi-device world. When it comes to Customer Experience, implementing an omnichannel edge into your marketing can set you apart from your competitors and build lasting relationships with your customers.
Survey data collected by our team at Monetate and WBR Insights for our 2nd Annual Personalisation Development Studyindicates that only 15 percent of marketers are observing and tracking customer sessions across two or more devices. When compared with industry data, they are failing to detect at least 25 percent of the sessions that are part of a multi-device journey to purchase.
Moreover, the move from specialised departments to cross-functional teams may postpone the personalisation process. For example, one team might be focused on website optimisation, while another team is solely looking at advertising display. Ensuring full alignment and buy-in across the organisation will enable a more seamless process where all teams can work towards a unified data and technology goal.
Master the visual
Whilst consumers expect a personalised experience, content does not have to be unique to each user to be considered effective. A collection of creative assets and copy relevant to a broad scope of interests is key to finding the right balance to appeal to individual users. It’s not just about the brand imagery, product recommendation, or message, but a combination of all of these elements, on the right platform, at the right time.
Achieving effective personalisation is challenging. As the Chief Marketing Officer of a technology company, I’m familiar with the challenge of finding the strategy that not only works, but also sticks. It’s easier said than done. The moment you implement personalisation marketing is the moment you change the way your customers view you – for good.
If brands can strive towards a future with machine learning and marketer creativity working hand-in-hand, they’ll see the benefits of increased loyalty and greater ROI more quickly.
According to a Salesforce Research paper published last year, 79 percent of customers now expect offers and recommendations from companies to be personalised based on what they’ve already bought.
It’s part of a trend we’ve seen emerging for years in commerce, a trend that is now beginning to reach critical mass. If a brand neglects to give their customers the uniquely tailored experience they’ve come to expect, they’ll simply find it elsewhere, usually with a competitor.
This failure to adapt to a modern customer experience is the downfall of many businesses that would otherwise have been very successful.It’s difficult for sure, but thanks to machine learning and AI technology, it’s getting easier. But what does it all mean, and where should businesses even start?
It’s hard to imagine in 2019, but transactions were once regarded as ‘one and done’ deals and had no deeper meaning or analysis attached to them. There was an exchange of product and money, and that was that. At most, a customer’s details might have been manually entered into a rudimentary CRM suite (Customer Relationship Management) where their file would surely have gathered dust until the business uncovered their email address to drop some random offers into their inbox in an effortto stir up sales.
Back then, this was the extent of the Customer Experience – detached, directionless, and oftentimes annoying. Customers never liked being sold to, and that’s even more true today.
These days, thanks to artificial intelligence and analytical technology, the insights derived from a transaction are almost becoming more valuable to a business than the transaction itself. The Customer Experience has been completely transformed, and if a business can anticipate a customer’s needs and present personalised recommendations based on transactional data, they’re far more likely to become loyal, repeat customers for years to come.
The modern Customer Experience is about removing purchase barriers, reducing friction, and making it easier for the customer to come to you rather than you necessarily going after the customer. For this to work, businesses need to start really getting to know their customers as individuals.
How can a national brand ‘get to know’ thousands, tens of thousands, or even hundreds of thousands of customers as individuals? Transactional data is fantastic, but it only really paints part of the picture.
To truly transform the Customer Experience, we need to know what customers are thinking and feeling. It sounds insurmountable, but it is entirely possible. It begins by extracting qualitative information from customers directly through things like feedback, ratings, and surveys.
This is the easy part. The difficult part is getting that information into a form that’s meaningful, measurable, and actionable.
Fortunately, machine learning is overcoming many of these difficult barriers for us. Using new technology, we can unlock the value in qualitative opinion-based input and apply quantitative traits that can be used to influence and develop services.
Essentially, machine learning helps make the immeasurable, measurable. Combined with natural language processing (sometimes referred to as NPL), machine learning is capable of extracting keywords or phrases from individual reviews, and then applying that same technique to large scale batches.
Once extracted, the context is considered during a ‘sentiment analysis’ which can determine whether items are being talked about positively or negatively. These two elements combined allow businesses to collect detailed feedback at scale, even picking up on certain elements that may have previously been overlooked. The frequency and context surrounding particular items can help steer the attention of the business in the right place, influencing overall strategy and behaviour.
As well as transactional data, which can help shape the individual experience in terms of predictions and buying patterns, machine learning can help shape the customer experience en masse and transform services to better suit the market. Extracting ‘in the moment’ feedback for immediate response is great, but there’s also a lot of value to be gained at other points in the customer journey, away from the transaction itself.
This ability to rapidly analyse thousands of customer touchpoints throughout their time with a brand can help that brand identify particular behaviours or sentiments as they are emerging.This is where data translates into valuable, actionable insight.
Similarly, the qualitative, opinion-based insight from customers could be combined with transactional data, stock levels, product specifications and even a customer’s browsing habits – all to deliver a service that preempts the customer’s needs and makes their decision to purchase completely seamless.
To see this innovative technology in full swing, we can turn our attention to the health insurance market. Some pioneering brands in that industry have embraced the Internet of Things (IoT) to personalise insurance policies and deliver value that specific to each individual.
For example, tracking heart rate data, step count and general activity through wearables can demonstrate that an individual is healthy and active, therefore granting them access to better deals and cheaper insurance. Effectively, it’s a way for health insurers to do what they’ve always done – evaluate risk – but with far more data at their disposal. Factor in other IoT technology such as smartphones and smart appliances, or black boxes on cars, and you begin to see how this tapestry of technology can be woven into a highly personalised and desirable service.
Regardless of industry sector, machine learning and natural language processing has been the missing piece of the jigsaw when it comes to providing a truly unique and customer-driven experience. Combined with data from other channels, customer insight is allowing businesses to learn more about their target market and break it down into very specific and detailed segments.
Not only can this inform business strategy and the development of services, it can shape all aspects of business marketing and give sales teams the insight they need to attract, retain and delight customers. The beating heart of this elaborate process is the customer experience platform – allowing verified customers to engage with brands easily and share their opinions on their experiences in a meaningful and valuable way.
Recent studies have found that over a third of the UK’s population have attended a festival since 2016, proving there’s always a fanbase ready to trade home comforts for a weekend of music, food, and drink in a field.
Yet while the demand from music-lovers continues to grow and organisers remain eager to meet these demands, it’s surprising that the outreach and sales process is still rather old-fashioned.
Festivals are big business, but margins are getting squeezed all the time. Glastonbury is the UK’s largest festival with a turnover of £37 million, but this only translates into profits of £86,000 – under 50p a ticket.
When looking forward to 2020 planning, event organisers should be looking for new opportunities to ensure they remain relevant and profitable.
With today’s technological solutions, event managers are not only able to get to know their customers better but also deliver the best, most satisfying fan experience possible through ‘conversational commerce’. When fans are having a good time they’re more likely to spend at festivals and continue to return for years to come. By rethinking how to approach and interact with fans directly – through bypassing costly and rather generic display social media ads and simplifying how payments areprocessed before, during and even after the festivities – organisers can achieve the ultimate fan experience.
The personal touch
Festivals are renowned for retaining loyal fanbases, with festival-goers opting to return to the same festival year after year for a guaranteed good time.However, with so much choice on offer, it’s proving increasingly difficult to ensure that your event remains top of mind when sales open for 2020 festival season. How you approach fans in the build-up is critical to whether they chose your event or a competitor’s.
Fortunately, by utilising the previously unused data collected the first-time round, you can create highly personalised and relevant content for the future. The true value of data is how it helps you get to know your customers on a personal level; what artists did they favourite on your festival app last year, and what drinks did they order? By collecting all of this data in a Customer Data Platform (CDP), it can help to determine which fans are the most likely to become frequent attendees for your upcoming events. Useful data – such as contact details, which tickets they bought and when – can be put to good use in building a loyal, recurrent fanbase.
Every customer is unique and so it makes sense that the way they like to be approached differs drastically. By using each customer’s unique data from the CDP, the fan’s preferred messaging channel established, and be used as the default route for engagement. Nowadays generic emails will likely end up deleted or in a customer’s junk folder, but by proactively approaching the fan on the messaging channel of their choice, that is tailored to the customer, you greatly increase the chance for engagement and conversion.
As the smartphone grows in importance as a basis for ticketing and customer engagement, channels like SMS – that still enjoy a 98 percent open rate – will remain important, but festival organisers also need to think of the future. There is a growing trend of a move towards Rich Communications Services (RCS), Apple Business Chat and Over-The-Top (OTT) messaging services like WhatsApp as customers seek greater convenience and the ability to transmit in-call media.
By catering to these rising services, organisers are futureproofing communication and engagement with customers by talking to them on their preferred platforms and ensuring that all personal data is collected, used and stored in GDPR-compliant manner.
Far too many event organisers make the mistake of completing their ticket sales and then dropping any form of customer engagement in the weeks and, sometimes, months between the point-of-sale and the festival kick-off. This period of time is an invaluable opportunity to build excitement in the fan leading up to the event.
Between the ticket sale and festival date, more information becomes known as bands are confirmed and merchandising and supplier deals are signed. Proactively communicating these updates via the customer’s messaging channel of choice will build their excitement for the event and help them plan their time for maximum enjoyment. What’s more, informing them of special deals and merchandise ahead of time will only maximise revenue opportunities once they get there.
Taking the stress out of payments
During the build-up to ticket release, most festivals will release teasers a few weeks prior and a couple of reminders a few days before. For the most popular festivals, hardcore fans will often queue up online hours before the ticket sales page comes online, constantly refreshing in the hope of getting ahead in the virtual queue.
This is an unfair and unnecessarily stressful process for the customer. The person with the fastest processor on their machine almost always gets their ticket first. As a result, the customers experiencing frequent disappointment, are left dissatisfied with the festival, increasing the likelihood of them giving up on ever trying to go again.
Fortunately, there are many ways to overcome these pitfalls. Once you have proactively reached out to festival fans, you can offer a preregistration by asking them how many tickets he or she wishes to receive and what kind. This way a fair drawing can be organised where everyone who preregistered gets the first opportunity to reserve tickets and a notification telling them whether they were successful. Additionally, new fan profiles can be created and added to the existing ones on the festival organisers customer data platform – all enriched and updated in real time based on customer preferences and purchase history, allowing for highly personalised engagement.
Fans will then receive a payment link on the same messaging channel they were first contacted on – or a different one based on their preference. You can set the system up so that if they don’t pay within a set amount of time the tickets are offered to another preregistered fan. Once payment is complete, the tickets can be sent directly to the customer or made accessible through a festival app or an OTT app of their choice. Organised and efficient solutions such as these are already being deployed by the likes of Formula 1.
The same app-based approach can be applied to customer payment solutions during and even after the event. By linking their account to the festival app, a customer can open a festival ‘tab’ to order refreshments and merchandise in-app, enjoy the festival experience and settle the bill automatically after the festivities are over.
This means no more standing in line to order, losing cash or having to shout over the music for a bartender’s attention. All fans need to do is show the QR-code automatically generated after making their order. As a result, fans have more time to enjoy their festival experience without the hassle of payments. This solution was pioneered by the organisers of Lowlands Festival in the Netherlands this year.
When payments is an effortless part of the fan’s festival experience, you’ve achieved true conversational commerce. When you cater to all communication channels and ensure payments processes are embedded in each, the customer can contact and do business with you the way they want. They have both the optimal Customer Experience and the incentive to come back to you again and again.
The new communication age
Personalised contact and conversational commerce are only the first step. If you want to understand your audience to their core, imagine all the other platforms your audience use and link them to their festival account. With the consent and approval of the fans, all relevant social media accounts could be linked to a single customer data platform. This way, you could analyse their favourite artists and make relevant suggestions to the customer in real time, such as which stage to visit and when to get the best views.
In order to deliver this next level communication experience, event organisers need one platform that ticks all the boxes – from data collection to messaging and processing payments. With the right tools and data infrastructure, however, the truly customised fan experience of the future is there for the taking.
At its best, science fiction taps into our contemporary anxieties to predict the fate of humanity.
An episode of Doctor Who, for example, featured robotised mega-corporations, human irrelevance, and despair. The Doctor may be sci-fi fantasy, but the issues are real.
Artificial intelligence (AI) technology is reshaping many sectors – for both good and ill. Gartner predicted that artificial intelligence would generate $1.2 trillion in business value in 2018 – an increase of 70 percent from 2017. But on the negative side, it creates much anxiety about the elimination of jobs, and prolonged focus on the cost and job-cutting aspects of AI has overshadowed how the technology can help human employees.
The CX example: how tools can hinder trade
In the customer service sector the rise in AI, decision-support, automation, and chatbots has exploded across the industry, driving multi-channel customer experience (CX). But adoption of these technologies for employee engagement has been slow. Contact centres have some of the highest employee turnover rates in the world, and there’s been troubling analysis suggesting new technology is inhibiting employee performance, engagement, and satisfaction.
Gartner analysis reveals service representatives use the mindboggling average of 8.2 different systems and tools during a customer interaction. Small wonder, then, that talk-time is up nearly 14 percent while call volume has remained the same.
We have amazing systems driving less-than-amazing experiences for the people charged with using them. A primary source of the problem stems from something obvious. We’re measuring the wrong things.
Just exactly what should we measure?
In our rush to capitalise on AI technologies, we’re failing to evaluate the way they ultimately integrate into human workflows. In the customer service sector, technology is better at handling many discrete tasks but does not replace human representatives.
It’s becoming standard practice, for example, for companies to host automated, largely self-service interaction options for customers that are always available. Digital account portals supply constant access and handy personalisation capabilities, while well-designed chatbots and virtual assistants are excellent at taking orders, payment processing, status checks, or informational queries.
But for more complex requests that require human nuance and context, technology-enhanced services can complicate the situation. When dealing with the customer, human agents are at a loss without access to what transpired during those digital interactions. And even when human agents can access those systems, they shouldn’t be flipping back and forth between applications and databases while attempting to deliver proper support to a customer.
This problem is perfect for AI solutions. Analytics engines that deliver historical and/or relevant customer information to support agents automatically and in real time can speed rather than delay productive conversation. Natural Language Processing (NLP) systems recognise spoken keywords and supply agents with useful prompts or notes, sparing them from app fatigue and task-switching. Virtualised on-demand training systems can keep them stimulated and engaged.
This employee-centric AI deserves more study and development. Systems that aren’t generating a positive Employee Experience will negatively affect the Customer Experience they deliver. Exploring ways AI can better serve employees is the solution. And measuring how employees view these tools should be the first metric for success, not an afterthought.
Collaborate to work out what best to measure
Applying AI to better serve the employee is crucial, but should be measured and managed with caution, given the enormous amount of data available.
One of the greatest struggles from an AI development perspective is determining how often a system should prompt the employee and whether there should be a trigger. Can such a mechanism be ranked? Do we allow the employee to turn off certain notifications because they’re annoying?
There’s a risk of overdoing AI assistance for Employee Experience. It could get very frustrating, very quickly. The only way to arrive at balanced employee-centric AI application is through collaboration. The people using the technology should have representation at the development table, which is also an excellent way to increase job satisfaction.
The future will require us to adapt what we measure
As AI technology becomes integrated into the enterprise, we must adapt how we gauge human performance. In CX management, technological innovation dictates that businesses restructure how they view customer contacts and the human staff who perform those jobs.
Contact centre positions will no longer be entry-level or outsourceable roles. With automation handling all the basic contact tasks, human customer service becomes a more specialised profession. Savvy and emotionally intelligent customer service employees with thorough understanding of a business and its technology will be a necessity. They’ll be managing only the most important, complex, or delicate customer concerns.
Today’s metrics, such as talk-time or calls-per-hour, provide little quantification under such circumstances – but the quality of this work will largely determine a company’s reputation among human beings.
Data harvested from Google Images has revealed the extent to which women around the world appear to be underrepresented in senior management roles, compared to the actual number of women holding these posts in real life.
Global data provider Creditsafe replicated a standard first impression for a search engine results page and looked at the top 25 Google Image results for the search term ‘CEO’ in 15 countries to see how many times women were shown.
According to statistics from the International Labour Organisation, women represent an average of 31.3 percent of the world’s senior business leaders. However, just 11.9 percent of Google Images results for the search ‘CEO’ were of women.
In the Creditsafe research, Colombia was revealed to be the country with the largest discrepancy between Google’s results (zero percent) with the country’s actual percentage of women in managerial roles (53.1 percent). Russia, Norway, Mexico, and Japan were the only other countries to have no female representation in their respective top 25 Google Images results.
The UK was found to have a negative discrepancy of just over 15 percent. With 34 percent of the nation’s business leaders being female, just 19 percent of search results showcased women in these types of leadership roles.
Meanwhile, Canada was the only country in this analysis to have a higher percentage of women in its Google Images than in real life (up by 2.68 percent). The United Arab Emirates (UAE) depicted the truest representation out of all countries referenced in the research, however, this was reliant on the country only having 10 percent of women in senior managerial positions.
Commenting on the results, Carys Hughes, CFO at Creditsafe, said: “Google collects images from sites across the web and shows an aggregation to users. If we want to change this, we need to ensure women are being represented accurately in our media, as well as our boardrooms.
“Data accuracy is crucial to our performance as an international business intelligence supplier. It allows our customers to make informed decisions to help grow their organisations and we think it’s astounding that the statistics are so far from reality in most countries around the world. Our analysis has revealed that once again a source such as Google is not always the most accurate and whatever we are researching always needs to be backed up with accurate and up-to-date information.”
It used to be that when someone said “AI”, images of sci-fi films came to mind.
Nowadays, the effect is more prosaic: it’s become de rigeur to use AI as shorthand for “business wonder cure”. When we hear “AI”, we know we’re supposed to see it as the answer to any and all business problems, whatever the industry.
At the same time, we’ve seen Customer Experience become the key differentiator in all sorts of sectors, but particularly retail. We all want to be treated as individuals and expect those we buy from to act as value-add service providers, not just vendors. That fact has fuelled the rise of AI as the perceived silver bullet for retailers – the more data you have at your disposal and the faster you can put it through effective analysis, the more likely it is that you’ll provide a beguiling, personalised Customer Experience and product offering.
However, AI is a term that’s used too freely. It has become confused with machine learning, losing its original meaning of a completely independent decision-making engine. True AI would make decisions based on so much information that you couldn’t know the decision it’s going to make before it makes it – much like a human being.
In contrast to that, current machine learning applications are very controlled – they put a set data flow through a known algorithm which auto-updates based on the results it receives, but they’re nowhere near the level of independence required for true AI.
There are good business reasons why AI remains in the realm of hype rather than frontline use, though. Financial services firms aren’t using AI, for example, because they can’t control its results – there’s too high a risk that mortgage applications could be affected by unconscious bias, for example.
The same risks apply to retailers. A good example of this played out a few years back when Amazon attempted to take the human element out of hiring. It took data about the type of people it had previously hired, processed it, and then set the resulting algorithm to hiring people. However, it ended up only hiring men – because that was what Amazon had historically done. It discounted women based on past experience, and therein lies the problem. AI based on past data doesn’t let you change for the better.
This kind of coded bias is also indicative of the people who’ve made the algorithm – if it’s a non-diverse group designing the algorithm, they’re more likely to almost accidentally code bias in. This is one of the main reasons why pure AI isn’t often used – the data you have might be biased, and you won’t know until it’s running. If it goes wrong, you can’t unpick it.
Think of it like a child growing up: once they’ve picked up negative behavioural traits, it’s very difficult to undo the hardwiring.
Despite all this, genuine AI is a possibility. The key is ensuring that applications have access to sufficient data – and the right kind of data. The more data you have, the more likely it is that you can build something that will provide accurate, non-biased results.
Unfortunately, we’re simultaneously seeing a sharp decrease in willingness to share data, as scandals like the Cambridge Analytica debacle damage confidence in the safety and privacy of large-scale data sharing. As a result, businesses have to navigate a very fine line between feeding enough data into their automated systems to achieve an optimal, non-biased Customer Experience and preserving customers’ privacy and trust.
Take the worked example of calling HMRC. As most of us will know, it can often take forever – it’s not a positive experience. To solve that problem, HMRC recently announced a desire to use voice biometrics for identification to speed up the process and remove the endless questioning. The system would be able to tell your mood, quickly identify why you’re calling, and put you through to exactly the right person to solve your problem.
The idea is a good one, but it depends entirely on people being comfortable sharing their voice data. Without that data, how do you optimise the system? As we move away from data-sharing as the default, how can companies still optimise Customer Experience with AI-driven technology?
Prioritising end users
In a nutshell, the answer is preparation. Lots of organisations come to my practice and say they want their customer journey to take advantage of AI and machine learning, but often they don’t have the tools in place to support it – no security, no data automation, and no clear understanding of the business need they’re trying to address.
They’re starting from the wrong point. Technology is not the end goal – Customer Experience is.
Companies need to start their AI CX journey with basic identity and access management. They need to inform their customers that they value their data and their security, and that they’re going to use their data with set controls in order to then keep them informed and give them proactive customer service, say.
Transparency is key – and you have to have the technology in place to back it up.
The bottom line is that an AI-enabled customer journey should always start with security. It’s essential to be able to protect your customer’s data as you use it. Not only that, but you need to make sure you’re providing a service that actually meets real needs, so find out what your customers want.
Start with their needs, not your technological goals. AI can take customer relationships to the next level, but it must be designed with the end user in mind.
Businesses in the UK today are very focused on bringing digital tools and tech into the heart of their processes.
You are a brave Marketing or Operations Director if you say that digital transformation is not at the heart of your 12, 24, or 36 month plan.
The benefits of embracing digital are observed everywhere: customers want to browse your products online, buy them online, find your store online, have their questions answered through prompt emails and chatbots, have their returns handled online, and so on.
And there’s plenty of tech vendors selling the dream – tech that enables and automates these processes – helping you to target customers with messages and offers tailored to their needs without any messy set-up requirements, easy to operate, cheaper-faster-better, and pain-free.
Sounds familiar…yet very rarely turns out like that, right? This is because you have to build your digital tech around the way your organisation works, not the other way around.
Less is more with technology, the focus is the customer journey
The reasons for disappointment in digital transformation projects are numerous, but at its core the problem tends to be the same – if you get to the stage where your people are supporting your tech instead of the other way around, you’re in trouble.
Many of our clients ask us for advice on their digital tools and data architecture and are frustrated that they have not obtained the benefits expected from their choice of Data Management Platform, or email service provider, or analytics package. Most often, the problem is not the tech, but the way that the tech has been configured (or not configured), compounded by the fact that the client has set up the tool in isolation from the other tools in their infrastructure. Buying new tools to replace and improve upon the tools’ already there is not the solution!
The solution comes from forensically focusing on identifying exactly what it is that the client needs to execute and configuring the tech for every use case. For large companies, this can require hundreds of use cases and data sets, and that can sound daunting. But that’s what’s required, for many reasons.
One specifically being it’s the law. GDPR requires all companies that hold customer data to have documented processes for the management and deployment of each customer interaction, by channel. To be compliant businesses need to painstakingly deconstruct and document the way they obtain, store, process and deploy their data in each use case anyway.
Another reason is that, whatever the martech salespeople say, the tools do not “seamlessly and automatically interface with your other tools”, or whatever other blasé statement they make to smooth the sale.
This type of mis-selling almost led to a disaster for an international client of ours embarking on a multi-million pound marketing transformation project. As we were specifying the solution, including tools and processes, our new client told us that one of the tools at the centre of their new process was being taken out of the scope, because they had been assured by the vendor that their tool would “set all the taxonomies for the data, and if anything changed, the tool would automatically ripple through all of the changes to the taxonomy…so we don’t think we need help with that”.
Fortunately, we had the experience with the tool and the communication skills to convince the client otherwise – the tool did none of those things and had no automated interface with the large number of data sources in the project. For the client, it was a near-miss; if we had accepted the claim of the vendor that the data would be set up and reconfigured automatically, the project would have been yet another digital white elephant, with everyone scratching their heads, asking what had gone wrong.
Businesses must re-think coordination and collaboration
The final ‘problem’ causing implementations to not go as planned is people. I like to say that any transformation project involves 30 percent of the work getting the tech set up right, and 70 percent “getting people to do things differently”. I’m not advocating that people’s processes and ways of working need to be radically reconfigured.The tools we use for digital marketing are not hard to use, and correctly configured, they should require little reskilling.
The core change that businesses need to make is around coordination: which means, getting people within and across teams to collaborate better, so that the business has a coordinated response to each customer interaction, rather than each team operating in its silo, sending emails, banners or coupons to solve each customer problem in isolation, because it is the only tool they have been given.
The key to success in deploying tools is for the business to be clear on the role for that tool and have a clear plan for how the data used by it will flow to and from other tools in the stack. You can be sure that you will be using different tools in a year’s time, so the instinct to make a decision that you can lock in for years to come is misguided.
You need a set of tools that remains flexible and focused on the tasks required, or you’ll soon find your infrastructure is out of date and not able to give your people the best available capabilities for serving customers. Tools should be just that – tools to do a job.
Businesses have been drowning in data for years, and in the CX space we’ve developed some bad habits, collecting information without any clear purpose and sending out surveys to ask for feedback at every turn.
Then, doing nothing with it, we are seeing the impact of this activity on both our customers (where is your response rate at the minute?) and our executives (how clear is your ROI?).
Fortunately, we have got better at using business intelligence (BI) solutions and best practices to try to make sense of all the data and to provide useful insight. The most successful at this have also taken the next step and been able to aggregate and harness the enormous breadth and depth of data to identify the drivers of business performance.
However, over recent years, there has also been a clear shift towards a focus on the customer. Also, while many BI strategies do incorporate customer data, they often don’t cover the full customer lifecycle; qualitative insights about customers; or, more importantly, the customer perspective when it comes to critical decision making.
Fortunately, the rise of CX programmes has enabled us to unleash the voice of the customer, providing a much clearer understanding of the impact that decisions will have on the customer (as well as team members, partners, and shareholders).
It’s for this reason that I suggest that CX should no longer be thought of as ‘a survey programme’ but as a ‘BI programme’.
Why? Because we are getting much better at wrangling the data, even when it is not all quantitative, and the evolution and convergence of BI and Customer Experience solutions means that they can help to trigger the data-driven decision making, which is now a pre-requisite of modern business.Adding the capabilities offered by CX technology and the skills of CX practitioners to the BI arsenal enables businesses to make better business decisions based on the entire experience ecosystem.
As a combined force, businesses can not only harness context-rich customer insight to drive better Customer Experience – they can also leverage the in-depth data and analytics needed to enable faster decision-making across all areas of an organisation, from employee engagement activities and product development through to distribution processes and beyond.
Delivering decision intelligence
In other words, the CX and BI evolution is enabling both CX and BI to be viewed from a fresh perspective.It’s no longer ‘just another department’ but instead it’s a strategic business function that empowers leadership teams to track trends and identify areas for improvement as well as motivating people to make a decision, to initiate and monitor organisational change.
There are two main reasons for this:
A shift away from a focus on collecting data to one in which the emphasis is placed on connecting data together to add context and make sense of their multiple sources.After all, data on its own, no matter how big or complex, is still just ‘dumb’ information.
A growing understanding that individuals across an organisation have shared ownership of the Customer Experience – not just those on the front line. As a result, traditional silos of data are being merged – whether that’s from customers, employees, partners, or suppliers; and whether it’s originally sourced as financial, demographic, or operational data.
Integrating and mapping these sources means that organisations are in a much stronger position to make data-driven decisions. Decisions that are enhanced with emotionally rich ‘stories’ or evidence. It means that everyone can visualise data points that are relevant, empowering them to take action within their sphere of control.
That is, after all, what the concept of business intelligence should be. There is no point in collecting data and regarding the reports that have been generated as ‘the result’ or focusing on short-term revenue growth.It’s just the start.
Insight for better business outcomes
The real benefit lies in providing companies with an increased capability to analyse the impact of actions and to ensure that they are having a positive impact on business results.
That’s because making better decisions is not enough – there needs to be a clear ROI, whether that’s in terms of improved service delivery, time and cost savings, better retention of employee talent, or any other business KPI.
That’s where CX once again steps up as an addition to the BI toolkit. By providing a structured framework for insight analysis, it’s able to provide the evidence that demonstrates a clear link between decisions and outcomes. It can also go one step further by enabling organisations to replicate and embed the behaviours that drive good outcomes, and minimise those that don’t.
The most deeply-embedded CX programmes have the power to ensure that everyone follows through with plans, actions are monitored, experiences shared and impact measured. As part of a robust BI strategy, CX plays a crucial role in keeping the focus on customer-centricity and enabling organisations to better understand how to drive sustainable, customer-led growth.
We’re flush with new ways to engage with customers, but businesses should be more data-driven, rather than simply throwing more manpower on the frontlines.
In the era of new contact centre touchpoints, the touchpoints themselves matter less and less because they should be managed in a unified way. That’s not to say we should disregard the touchpoints – in fact the opposite is true. We should be able to add them and monitor the data from customer interactions to create contact centres that offer better service and embrace innovation when it comes to engaging with customers.
In real terms, that means putting an end to seeing telephone, web chat, or mobile app communications as an island in their own right. Each channel will have its own considerations and technological challenges to take on board – that much is true. Yet as agent desktop interfaces better integrate the new channels that emerge, we should start to think of how we can solve new business challenges and get smarter, as well as becoming more efficient.
Hearing the voice of the customer
For many contact centres, voice has been their bread and butter for years. The difference now is that voice is used less – at least in its traditional sense. Meanwhile, phones are being used in different ways, particularly with the growing use of smartphones. Voice now has a closer relationship with other digital channels, and as a result, firms should prepare all channels to account for customers flowing between each.
Although customers are generally using phones less for voice calls than they used to, we’re now seeing an increase in phones being used as a digital backstop. If a customer doesn’t get the response they expect from digital channels, they will probably pick up the phone to speak to an agent. This brings to the surface the importance of managing the two types of contact centre interactions – those driven by bots and those driven by humans. Human agents will want to deal with the queries where they feel like they can add value. The simple issues such as the loss of a password can be dealt with automatically.
Agent time is both precious and costly and so should be used for issues where it is necessary. It’s important then, for businesses to find the right match between interactions handled by chat bot, and interactions that require a human touch. The best approach is to use a mix of both, where bots escalate to an agent when needed, without customers feeling like they are being passed between non-connected entities.
We also have to prepare for a new era of voice interaction. There were 9.5 million active smart speaker users in the UK last year, which is an increase of 98.6 percent against 2017, according to eMarketer. Consumers are getting more comfortable in asking these devices to perform basic tasks and provide them with information. The next step is for them to be the conduit to getting in touch with the outside world. That doesn’t just mean communicating with close friends and family as is the case now but increasingly, with brands. In fact, voice assistants are just one part of a larger move towards a more integrated IoT service, which also includes connected cars.
We’re using bots to answer more customer questions with speed and accuracy. Doing the same thing with voice-activated devices will cut out the middle-man where needed, while still basing the approach on the voice model that has operated in contact centres for years. But as with any channel, it’s vital that voice plugs into a bigger picture view of customer interaction. Omnichannel rules the roost and provides a great deal of insights that are valuable for businesses.
Data insights enhancing Customer Experience
On the whole, companies have to get better at proactively engaging with customers and artificial intelligence (AI) will help to do this. For example, with the right data coming from previous customer interactions and insights it is able to obtain from initial contact, AI can be used to provide a more targeted response, and through a combination of virtual assistants, machine learning and customer data analytics, businesses are able to predict customer needs.
Not only that, they can proactively address these needs to prevent repeat contacts for similar issues, deliver superior experiences to retain existing customers and improve offers or interactions in a way that attracts new customers.
There’s also the intelligence that businesses can uncover to shape their products better – all from the way they monitor customer interaction. When firms automatically capture and analyse interactions, they can make sure they never miss the vital signs that should be spotted immediately. They are able to identify gaps in products, processes, and interactions – and make sure agents meet the needs of demanding customers.
One of our customers is a coffee company who was looking to carry out a strategic launch of a premium product. They automatically analysed all their calls and as a result, they were able to better train underperforming agents with targeted coaching. By analysing interactions at the contact centre, it enabled them to better understand how agents were pitching the product and it also helped them to see how well the new product was being perceived. Using these measures, the company increased sales penetration using best practice, and increased basket size by pushing promotions at the right time.
I’m excited by the prospect of new touchpoints and technologies coming together to offer a better service to customers, better performance for agents and better efficiency for businesses. And with voice assistants, IoT and other connected ways for businesses to interact with people, the whole area of customer services has been blown wide open. There’s so much potential for innovation.
But with all these touchpoints, it’s vital that businesses can connect the dots across the different channels they use. It’s an approach that includes not just the communications channels but the knowledge captured from CRM systems and contact centre insights. We know that the channels will probably change in the future as consumers find new ways to interact with brands but in the grand scheme of things, that shouldn’t matter. What is important is a technology agnostic approach through providers that incorporates the channels, and provides a single dashboard that enables businesses decisions to be made based on insights, rather than just intuition.
The thing with data is that the findings are hard to dispute, so long as you are confident in the original sources, sensors and algorithms. The future won’t necessarily be dictated by the latest flashy communications channel. Instead it will be led by smart approaches, and increasingly, that means taking steps to focus on automation, analytics and innovation of Customer Experience in a meaningful way.
The digital landscape is continuously evolving and with that the volume of data created and shared grows exponentially month on month.
High profile data breaches and the implementation and enforcement of GDPR have really brought home to customers that their data is of enormous value and that they have explicit rights to consent to its storage and use.
For millennials and Gen X, who may have had the comfort of growing up around emerging technologies and the birth of social media, the use of data may have been apparent early on. Online domains have further highlighted that data is being collected and used to match people to the products it assumes they either want or would like.
When it comes to personal finances, this can be a prickly subject, as in the past major data breaches and mishandling of data have eroded customer trust. However, when handled responsibly, customer data can be used by personal finance providers to offer better solutions and outcomes – something many customers have yet to realise.
Trust in a business and its services is essential to success. In personal finance, it’s about giving customers the tools they need to feel fully in control of their finances, whilst still making sure that there’s people on hand to help. Human interactions are still as important as ever in the financial decision-making process. With that in mind, having someone in your business to bridge the gap between customers, their data and the regulatory landscape, is crucial. That’s where the Chief Customer Officer comes in.
One prime example of the advantages data can bring for customers, is the innovation being made possible by the UK’s Open Banking initiative. People have become increasingly aware of their personal credit scores thanks to a host of places offering free access. In some cases,historical credit data alone may not be enough to satisfy a card, mortgage or loan application – and in those cases, Open Banking has been revolutionary.
A lot of what’s required to determine whether a product is suitable can be found in an applicant’s bank account, where evidence of income is relatively easy to verify. Those with thinner credit files or irregular incomes, such as the self-employed, people new to the UK, or younger borrowers who are yet to build a comprehensive credit file, have the most to gain from Open Banking. Through this route, the data gathered, allows a better sense of an individual’s income and expenditure, resulting in the best possible product being matched to that person.
Open Banking is used as a tool to complement existing practices, allowing a more comprehensive view of a borrower’s information and circumstances, that couldn’t have been achieved through credit data alone, to present a better, broader and often cheaper range of personalised offers.
In recent years, the regulatory landscape has become much more consumer-centric, as seen by the likes of PSD2, a directive that ensured consumers were protected in a more digitised sphere. An era of block consent is being superseded by one of explicit individual consent. Organisations who embrace technology, are paving the way for future innovations and as a result will be able to deliver a higher degree of personalisation for each customer.
Customers can now choose to unlock the power of their data for their own benefit. Data is set to work towards their preferred outcomes and not merely to enrich those organisations with the privilege of accessing it. By experimenting with Open Banking and cloud services, Freedom Finance has been able to make the borrowing process easier for customers, while at the same time delivering a customer journey with consent at its core.
Customers of the future will demand better services that reflect the technology available. The challenge will be for all businesses, not just financial services providers, to find how the best elements of that technology can be combined with human guidance.
There are few better ways of minimising costs than offering products straight to buyers – and it seems brands increasingly agree.
Survey’s suggest nine-in-10 plan to launch their own direct-to-consumer channel (DTC), and at least 23 aim to do so in the next 12 months.
But the value of DTC goes beyond its profit-boosting potential. While the rewards of cutting out stores and retail partners can be considerable – see Huel, the powdered food brand soon tipped to reach £45 million in annual turnover – going straight to the source also allows brands to simplify consumer journeys and forge closer relationships.
Success, however, depends on authenticity. Vital to the lure of DTC offerings is uniqueness; consumers are drawn to individual brands that connect with their specific needs and values. So, when it comes to experience, every interaction must be personally meaningful.
The question is – how can brands consistently achieve the personal touch?
Discovering your own data goldmine
The first step towards better DTC experiences is harnessing the assets brands already have at their fingertips. Streamlining the supply chain provides more than simply a chance for independent companies to compete with large corporations; it also offers access to precious data. Because they deal directly with consumers, information about purchases, preferences, and habits flows into their own insight pools, instead of filtering down in fragments from interim partners and stores. As a result, they have a wealth of high quality, first-party data that can be used to gain deep understanding of customers and prospects, and inform marketing and sales strategies.
Utilising machine-mined intelligence
By far the most efficient tool for unlocking the valuable insight data repositories contain is artificial intelligence (AI). More specifically: sophisticated analytical platforms powered by AI subsets, such as machine learning (ML). Contrary to expectation, the main reason for this isn’t the high-speed, large-scale processing ability of smart platforms – although it’s worth noting ML initiatives have driven a 90 percent reduction in analytical run time. It’s the capacity of ML platforms to autonomously learn from experience and make fast, informed decisions. From a DTC perspective, this means ML can pave the way to delivering exactly what their customers want: authentic experiences with real-time relevance, and personal resonance.
Fuelling creativity with data smarts
The best-known use of ML as a driver of personalised interactions is dynamic creative optimisation (DCO). Essentially a smart matching process, DCO involves evaluating several data sources – covering contextual, demographic, and behavioural information – against varied creative elements. Its main aim is establishing the best blend of imagery, format, and background for specific consumers, in line with their unique attributes, such as individual preferences, location, language, activity, and progress along the path to purchase. For example, if a returning mobile site visitor is scrolling through product reviews and has previously viewed explainer videos, it’s likely a short-form testimonial video will be the ideal fit.
Understanding the optimal format to deliver your brand message to the consumer so that it is relatable is another consideration for brands that are taking the DTC plunge. Video advertising has become a key focus for a number of organisations, with an estimated 26 percent of the total video ad budget in the UK to be spent online. The ability to use data-driven insights to deliver these creative and personalised ads to consumers at the right time will help develop positive associations with brands and provide a competitive edge.
Deepening bonds over time
A combination of digital formats such as display and video ads, delivered to the consumer at the most relevant times, and including content based on detailed audience data, will help build brand awareness and consumer relationships in the DTC sector. By collecting insights about which strategies, message types, and offers work, brands can continually optimise interactions to ensure relevance increases over time. All of which will steadily strengthen the direct bonds between consumers and brands, driving lasting loyalty and value.
DTC is certainly proving to be an effective means of minimising journey friction and standing out in an increasingly competitive market. But to ensure consumer relationships stay close and profitable, brands must ensure the experiences they provide are personal enough to keep individuals hooked; and that calls for machine-powered intelligence. Only with a combination of AI-fuelled analysis, tailored messaging, and creative communication can brands maintain a direct line to consumers who always come back for more.
The impact of poor Customer Experience is not one easily forgotten.
The reality for retailers today is that for even the most loyal customers, one bad experience is enough to make them abandon their shopping baskets and never hesitate about returning.
Modern customer expectations are undoubtedly at an all-time high. Not only do consumers now have preferred channels, they also expect brands to deliver the best possible service across all channels, at all times. According to research by Walker, expectations have amplified so much that by 2020, Customer Experience is predicted to overtake both price and productas the leading differentiator for brands.
To meet this demand, retailers are ramping up their investments in omnichannel to deliver the exceptional experience customers now require. As technology continues to advance, the value of omnichannel continues to increase and retailers have begun to invest significantly to integrate both front and back end systems.
The era of omnichannel
Gone are the days where physical and digital channels work in silo. The world has evolved into an omnichannel environment, where the boundaries between online and offline have become blurred. At present, this presents both a challenge and an opportunity for switched-on brands.
A successful omnichannel experience is made up of individual customer touchpoints, over a variety of channels, that allows users to move from one channel to the next seamlessly, whilst maintaining a continuous thread of communication. Being able to provide this single congruous shopping experience is crucial to keep up with customer expectations and continue to grow the bottom line.
A diligent and well-thought-out approach is key to creating a strong omnichannel experience. Companies are now recognising the central role technology continues to play, and the importance of moving in-line with new disruptive technologies available to help them achieve an effective omnichannel strategy. Over the next few years, global analyst house, Gartner predicts that AI will become a mainstream Customer Experience investment, while 47 percent of businesses will use chatbots for customer care, and 40 percent will deploy virtual assistants.
However, rather than just rushing to implementing the latest and greatest functionalities to disrupt the market out of fear customers will demand it, omnichannel is as much about what to avoid, as it is what to include. Rather than attempting to do too much, too quickly, the key to success lies in always having the core needs of the customer as the driving force behind any change. Failure to do so can compromise Customer Experience, negativity impact brands, and shake up customers’ loyalty.
Using data to enhance Customer Experience
At the heart of strong omnichannel customer engagement is the data that drives it. In today’s competitive environment, the customer insight that brands are able to glean from different touchpoints can make a huge difference in how a company shapes its CX.
The digital environment produces mass amounts of data, and finding new ways to understand customer needs, buying habits, likes, and dislikes can help inform and enhance the personal experience brands deliver, allowing them to develop that much sought-after loyalty between brand and customer.
Data can help dramatically improve the customer journey, but only for brands eager to be led where the data instructs them to go. Those still focused on holding onto legacy structures, or past ideas, products, or services, will not find as much success in Customer Experience enhancements, simply because of their resistance to change with the evolving market.
For those switched-on brands that collect and interpret omnichannel data correctly, they have a more holistic and informative view of their customers and are better equipped to deliver more personalised and targeted offerings, streamlined buying processes and develop new customer services in the future.
Customers at the core of omnichannel
The power that consumers now hold shapes not only the success or failure of a brand, but also shapes how they need to adjust to customer requirements in order to remain relevant. Modern customer journeys aren’t simple and linear, but a series of crossovers between traditional and digital channels that can vary significantly depending on the type of shopper. Understanding this requires in-depth knowledge of what customers truly want by utilising the data readily available to them.
While new and exciting disruptive technologies may seem appealing, to leverage the maximum potential of an omnichannel strategy, brands must focus on getting the basics of CX absolutely right first by always remembering the core needs of the customer. Only then can companies ensure they keep pace with the competition and provide a seamless customer experience necessary to drive consumer loyalty today and over the years to come, as new technologies become more and more prevalent.
Anyone who has booked a flight recently will have likely noticed the level of personalisation creeping into their travel experience.
Even before you’ve settled on timing or your destination, airlines are tapping into yourintent, with some shrewd speculative interventions.
For example, if you have ‘liked’ a resort on Instagram or Facebook, you may find yourself targeted by an app that provides all the options for getting there, followed by itinerary recommendations via TripAdvisor. It seems all the main players in the travel ecosystem suddenly ‘get’ you and are able to anticipate your plans and preferences.
Advanced analytics that can glean deeper actionable insights from customer data are fuelling this transformation, compounded by greater industry-wide collaboration, and improved sharing of this intelligence. The result is more relevant products and services which have raised the bar of personalisation, along with the expectation that the personal touch shouldn’t stop when we book our travel plans.
If we stay in the realm of travel, we can see how this extends to the hotel sector. For an industry outside of the high-end luxury segment that has taken a one-size-fits-all mentality, it poses an interesting challenge.
This shift is set to disrupt some of the familiar routines that have long been part and parcel of the hotel experience. Think of the multiple adjustments that we make to a room on arrival almost on autopilot – the swift rejection of the wrong pillows and hair products that don’t fit our unique preferences, the trial and error that goes into resetting temperature, often with limited success.
It’s a routine on the cusp of being rendered entirely redundant if data collected prior to arrival based on previous stays can inform the housekeeping team of a preference for non-allergenic bedding or a particular branded hair product.
Behind the scenes, data platforms are doing the heavy lifting, with advanced analytic algorithms that combine customers’ historical engagement data, purchase history, digital behaviours, and environmental data. Predictive analytics then inform the kind of contextually-rich engagements that add value, ramp up the convenience and comfort factor, and provide a meaningful connection that can differentiate an experience in a saturated market.
And it needs to; customer expectations have changed irreparably!
Digitally-empowered and more discerning, consumers no longer fall into the crude categories based on gender, age, or marital status that were once used to determine rudimentary personalisation. In short, they know what they like and what they don’t; who they are and who they’re not. Today’s consumers expect to be treated as individuals rather than a segment, and with intelligence, relevance and empathy.
Yet there is still a fine balance to negotiate to ensure that such intervention remains engaging rather than intrusive and creepy – a trend often rooted in data overload and a heavy-handed approach to its personalisation.
Without question, we’re in a world of big data, where gathering ever-rising volumes and the ‘more-the-merrier’ ethos, can be the default approach to throw at any issue, sometimes at the expense of consumer consent, internal ability to act on the data, and ethical practice to how the data is applied.
Manyorganisations are struggling to manage the data they hold. Common challenges include navigating through too much data, managing the complexity of data, determining which data are appropriate for decision making, and upholding the security of data in an increasingly dangerous world of identity theft and fraud.
Nowhere is this more challenging than in financial services, where major decisions of credit worthiness, loan pricing, and customer service are increasingly based on analytics from integrated, intelligent data platforms; and where sensitive data must be protected from fraud and other cybercrimes. No wonder regulators are also balancing the need to protect personal data from both discriminatory decision making (e.g. the use of gender in insurance pricing models) and the rules for data protection.
It’s a reminder of the need for big data to become ‘impactful’ data, in order to cut through the excess and address the data basics; clean it and make it available to run in advance analytics platforms. Injecting a big dose of transparency into the process, by taking the cue from the customer in terms of the financial information they are comfortable sharing, is the next consideration. While this might be a slower burn approach, it is one that is fundamental to developing and instilling the requisite levels of trust.
Crucially, a common dominator of all this activity is the investment in time and commitment. Personalisation by its nature is not a quick fix; it demands innovation on multiple fronts if is to be applied successfully. Furthermore, technology cannot thrive in isolation and must be supported by a broader cultural shift that sees all staff committed to the process.
Returning to the hospitality sector, it is notable how many of the intuitive service touches depend on both the observations and initiative from front line, customer facing teams who are best placed to notice the small details and act on them directly with the guests. Ensuring they understand how their actions can resonate and be informed by the technology to build on this further, is a crucial piece of the jigsaw.
Being mindful of the pitfalls, while being open to embracing the innovation at our disposal, is a tightrope to negotiate, but once achieved can deliver the CX breakthrough on everyone’s wish list.
International CX management firm Assist Digital has acquired world-leading consultancy IG Group UK Ltd.
In a move which positions the company favourably in the rapidly growing global Digital Transformation market, Assist Digital is looking to widen its skills base and strengthen its presence in the UK and wider European markets.
With its headquarters in Italy, and a presence in France and Germany, Assist Digital plans to take advantage of IG Group’s impressive client portfolio of leading global brands. IG Group’s expertise spans a broad range of complementary capabilities, including an accomplished data analytics department, extensive business transformation experience, and a contemporary CX practice.
The purchase follows the recent acquisition by Assist Digital of French UX design company Attoma.
Speaking of the company’s latest acquisition decision, Enrico Donati, Co-Founder and Executive Chairman of Assist Digital, said: “Our focus as a company is on the whole Customer Experience management process. The complexity of today’s digital and multichannel reality requires ever greater design capabilities to offer customers simple, effective and intuitive solutions. The IG Group’s significant global customer base, knowledge and strength in analytics gels perfectly with our existing skill sets.”
Matthew Ellis, Managing Director of The IG Group UK Ltd, added: “This is a defining moment for our company and one we’ve been building towards for the past decade, which has seen us focus on enabling clients to make strategic sense of their data.
“This exciting acquisition enables us to make our proposition even more tangible and current, helping clients to realise the potential of their organisation. It clearly strengthens both companies and provides the springboard we need to move to the next level and dominate the market still further.”
It is clear we are racing head first into a data rich world, meaning businesses cannot afford to mis-manage their customer data.
Customer data management is a fundamental part of a company’s marketing strategy, as 83 percent of companies expect data and analytics to become more important in the business decision making process over the next five years. Optimal data management practices equip a company to gather insights which can be used as the cornerstone for Customer Experience improvement initiatives.
Improved Customer Experience is a clear-cut way to keep customers buying, thus increasing businesses’ revenues. However too many businesses are struggling with how to make sense of the available customer data; they lack the ability to merge cross-channel data thus hindering their ability to draw meaningful insights and consequently optimise revenues.
Therefore, it is of paramount importance for investors to include searching questions on good data practice as a standard part of their investor briefing. Asking the right questions will elicit the necessary insight for investors to determine whether the data management practices embedded at the target business are as mature as they should be and whether they will have an influence on the return on investment.
Here are five crucial questions which (institutional) investors can pose to corporations to better understand how well a business is managing customer data and whether or not their investment is well placed.
1. What is your share of customer?
It is crucial for investors to understand whether the target company knows their customers’ spending profile, the reason being to understand what potential ‘share’ of the customer’s wallet the target company holds. Customers split their spending across varying providers on a day-to-day basis therefore knowing the share the target company has of each of their customers will help investors determine the growth potential for those customers.
If a target company is able to demonstrate to an investor where the growth potential lies, it will show investors that the target company has access to fundamental insights on customer data and thus are well placed to grow the share of customer further.
2. Are newly acquired customers still buying a year later?
Continuously putting effort into acquiring new customers can be an expensive undertaking for some businesses, especially if those customers are not staying for the long-term. Investors need to look past whether the target company is offering sufficient customer acquisition incentives and focus on whether newly acquired customers are still buying a year later (and more). Customers who disappear shortly after acquisition highlight to investors that marketing spend is being wasted.
The target company should have the necessary data to highlight to investors that they have a proper grasp of their customer insight. Therefore questioning whether a recently acquired customer is still spending a year later will show whether the target company is using customer insight properly and will help gauge how the company will fare in the long-term.
3. Who are your best customers?
Collecting and analysing the right customer analytics will arm the target company with the crucial information needed to see if it is recruiting the best customers to fit the business’ priorities. Typically there is a key group of customers who contribute the most to profits; usually they buy high-margin products, don’t alter or abandon an order, pay on time, and don’t require much attention post-sale.
It is important for investors to ask this question so they can see whether the target company is wasting its time on a cohort of customers who in actual fact turn out to be the least profitable. If investors have clear evidence that the business knows what type of customer profile to keep targeting then they can be reassured about long term growth.
4. Which customers are in growth or decline?
A critical question not to be ignored. If the target company can report that its best customers (high value, high loyal) are in decline, then it is important that customer data is being used appropriately to reverse the trend. It may be the case that these customers are demanding discounts or are just looking elsewhere in the market.
The key for investors when asking this question is to determine whether the target company is using customer insight to pursue look-alike customers. Has a particular group of slightly less valuable customers been targeted with internal growth strategies to replace the declining group with potential high value and high loyalty contenders?
5. Do you have an integrated online and offline view of your customer behaviour?
When it comes to enquiring about the target company’s marketing strategy, the key for understanding marketing success is seeing how much incremental revenue a company’s marketing activity is generating. Any savvy investor will know that incremental revenue trumps isolated marketing campaign measures such as response and open rates.
Customers are influenced on a day-to-day basis by a variety of channels, and as confirmed by our latest research it is companies who combine online and offline methods who produce the highest commercial results. There are now a variety of techniques for harmonising all behaviour/transactions of a given customer into a single, integrated, 3600 view, and only if the target company can achieve this (and demonstrate this) will customer insights be valid and actionable.
Deciphering whether a business has a well-implemented and well-managed strategy for managing their customer data is critical for any investor, as the potential for future growth will be apparent. More and more customer data is becoming accessible and it is up to businesses to collect, analyse and use it to bolster their marketing strategies. Investors need to probe the business for their key customer figures to establish how advanced their customer relationship strategy is, as well as identify which tools are in place to effectively manage and analyse the plethora of available multichannel data for future growth.
Using the above five questions will help investors to get a feel for how mature a company’s customer insight management processes really are.
A new report has found that 20 percent of marketing and CX professionals feel they will “never truly understand” their customers’ buying decisions.
The study from analytics firm Clicktale, titled Defining Digital Experience, states that part of the reason for this is due to 34 percent of marketers and CX professionals being unable to unite data between their web and mobile-optimised sites to create a single customer view, while 39 percent struggle to unite data from their websites and mobile apps.
This inability, the report continues, also means that 71 percent of brands can’t action customer insights in real time, while 73 percent are struggling to provide a consistent experience across channels. Ultimately, this lack of ability to understand customers is hindering brands’ chances of securing customer loyalty and damaging potential sales.
The study explores the current state of digital with 200 marketing and CX professionals working in some of the world’s leading brands in the UK and the US. The report uncovers how brands are building a strategy around Digital Experience, including who is ‘owning’ the function, and what technology they’re deploying.
Clicktale CMO Sara Richter said: “With so many brands struggling to build a single customer view, is it any wonder that marketing and CX professionals feel they cannot build a true understanding of their customers?
“But while uniting data is undoubtedly key, so too is capturing the right kind of data – beyond the usual demography, geography, purchase history and preference. Very few brands are tapping into the power of behavioural data, which enriches the marketer’s understanding of the customer immensely. With behavioural data and the right analytics, brands can better serve customers, improve loyalty and drive more repeat revenue.”
Spring has certainly sprung in the UK and many high street retailers will be looking ahead to how they might refresh and renew their offering to entice customers.
The pressure remains high for bricks-and-mortar retailers as well as online brands following a challenging previous year of sales and increased competition. Over the festive period high street brands overall saw store sales drop by 1.9 percent in December for the sixth year running and there was a surprise profit warning from ecommerce leader Asos.
The high street is at a turning point and stores must adapt to reflect shoppers’ changing tastes and habits in the digital age. Offline and online shopping have their unique challenges, yet incorporating cutting-edge WiFi connectivity and analytics in-store is a simple, powerful, and cost-effective way for retailers to maximise the benefits of both channels.
WiFi connectivity enables retailers to revitalise their store by taking it online and delivering the ultimate best-of-both shopping experience which adds personalised value for today’s consumers.
A straightforward shopping experience
It is time to spring clean the in-store experience for customers who prefer simplicity and effortlessness over busy department stores. With no time to waste, busy shoppers will appreciate in-store WiFi to quickly browse the retailer’s online site for more product information or perhaps order a product which is out of stock in-store.
Connectivity is also important for customers to access order details if they have chosen a click-and-collect service, whilst WiFi supported messaging services allow shoppers to quickly communicate and get opinions from friends and family. Spring means new product launches and promotions and it can be a challenge for retailers to drive sales. Therefore, to attract modern time-pressed customers, the physical shopping experience has to be quick and effective.
Seventy-one percent of shoppers say they use mobile in-store, with 83 percent in the 18-44 age bracket, confirming that mobile is a key platform for engagement between retailers and customers and providing a robust connection will help drive customers into your shop. WiFi makes it easier for shoppers to log into mobile apps and consult the latest offers or perhaps the Wishlist they made at home.
Retailers should not forget that their ecommerce site works in tandem with their store and this is never more important given the current cross-channel competition. Maximising your WiFi means increased sales volume across digital and physical channels and increased customer engagement.
Shoppers increasingly prefer a self-service approach in retail and WiFi connectivity provides the ease and flexibility to browse from their smartphone. Simple digital tools such as in-store WiFi enabled tablets for self-service help customers to access whatever they might need whilst shopping and saves them time.
New consumer tastes deliver deals and discounts
Consumer confidence is struggling amidst economic uncertainty and retailers need to energise their services with something customers can trust, which is where providing value for money becomes critical.
We are a nation of increasingly savvy shoppers, scouting the best discount codes and promotions to lower the costs. For instance, while Barclaycard saw a 20 percent increase in the number of transactions over Black Friday from 2017, the amount spent dropped by 12 percent. Retailers can deliver competitive prices, which is especially important for today’s customers, and make promotions as accessible as possible by promoting their discounts as soon as customers walk in store via their WiFi’s fully-branded User Experience.
Greeting the user with the latest news and promotions once they log into the WiFi User Experience will increase the likelihood of sales and impulse buys, whilst also creating a more personalised experience. As one of the key consumer trends, personalisation helps to strengthen the brand-customer connection and drive customer loyalty.
Although retailers are struggling, the high streets are still crowded with options for shoppers, twice as many as need be according to one report, and retailers will want to ensure customers choose their store above others. Maintaining loyalty is critical for high customer retention and stores might consider loyalty programmes and incentives integrated directly via the WiFi or available on apps which can be accessed via in-store connectivity. The best loyalty programmes will use multiple methods to encourage users to shop with your brand again and again.
Get to know your customers in 2019
Seamless WiFi connectivity is a great incentive for customers, but it can also enhance your understanding of what customers want thanks to advanced WiFi analytics. The identity of the modern shopper is changing. Today’s consumers are heavily influenced by brand experience and stores which offer memorable experiences, whilst less disposable income means customers want well-priced, quality products. Any insights on how customers engage with your store will help brands to meet expectations.
WiFi analytics reveals data such as how many people enter your store, their average dwell time, which department sees highest footfall and the most popular marketing subscriptions, insights which can influence store layout and targeted promotions to better serve the customer. Data analysis can make a great difference for retailers and enable them to provide a more competitive service.
The way shoppers browse and spend is always changing according to the time of the year and continually analysing insights on how customers interact in-store will help retailers to improve the Customer Experience and how they relate to their customers straight away.
Shoppers’ brand expectations are increasing at a rapid pace, with cutting-edge WiFi high-street stores can not only deliver the mobile connectivity which customers demand but also have a detailed view as to what customers will want next and why.
In the current dog-eat-dog climate of the high street, where competition for increased footfall is rife, ignoring the potential benefits of digital connectivity could sound the death knell for many businesses commercially speaking which is why they need to act now to avoid being a casualty.