Customer Feedback Data: Creating a More Individual Experience

November 4, 201910min

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 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.

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.

But how?

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.

Insight: Knowing what customers are thinking and feeling is crucial for brands

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.

Neil McIlroy

Neil McIlroy

Neil McIlroy is Head of Product Innovations at Feefo.

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