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.
A trend we’ve seen emerging for years in commerce is now beginning to reach critical mass. If a brand neglects to give their customers the uniquely tailored experience they expect, they’ll simply find it elsewhere and 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. Gathering customer feedback and acting on it to tailor products and services is quite difficult. Machine learning and AI can help, but some are still wondering where should businesses start in designing the customer feedback strategy?
Modernizing your customer feedback strategy
It’s hard to imagine in 2021, but transactions were once regarded as ‘one and done’ deals. They had no deeper meaning or analysis attached to them. There was an exchange of product and money, and that was it. At most, a customer’s details might have been manually entered into a rudimentary CRM suite (Customer Relationship Management). The file would surely have gathered dust until the business uncovered their email address to drop some random offers into their inbox in an effort to 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.
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 customers to come to you rather than you going after them. For this strategy to work, businesses need to start really getting to know their customers as individuals.
Relying on technology
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 solutions 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.
How can machine learning help?
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, a ‘sentiment analysis’ considers the context, 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.
The importance of having a swift customer feedback strategy
This ability to rapidly analyse thousands of customer touchpoints throughout their time with a brand can help brands 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. This is all aimed 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 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. This allows brands to offer better deals and cheaper insurance. Essentially, it’s a way for health insurers to do what they’ve always done – evaluate risk – but with far more data at their disposal.
Creating more individual experiences
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 informs customer feedback strategy and the development of services but it shapes all aspects of business marketing and gives 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.