Using data to shape your customer experience

20 October 2017
Sam Miller
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The impact of having a seamless and engaging customer experience is no longer negotiable in delivering business results. The only problem is that actually delivering this customer experience isn’t easy without the right blend of technology, data and operations. In other words, a customer experience platform.


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The CX platform provides data, with customers leaving a digital footprint; their actions furnishing organisations with collectable behavioural traces. These interactions create hugely important first-party data, which is powerful, as it is the most relevant and accurate.

Leaving aside the technology and operational variables of the CX equation for now, I’d like to focus here on improving the value contribution of behavioural data in driving your CX.

Data is the key to unlocking utility and relevance, two of the core tenets of a great customer experience. It allows you to know your customer, learn more about them and act on it. Sounds simple? In theory, yes but, in practice, there are always a few challenges:

Freeing the data

The first challenge for using data in your CX is getting it the attention it deserves against the competing pain points of a fragmented technology landscape and the siloed nature of many organisations (as discussed previously on the Cog Blog). Who extracts the data? Who owns the data? Who should use the data? It can be hard to even answer these simple questions in large organisations.

Is it the right data?

Organisations have increasingly realised the value of behavioural data and more and more is being collected; the big question is whether it’s the ‘right’ data. What do we mean by this? Is the behavioural data you’re collecting going to answer the questions that you want to be answered?

Reconciling behavioural data into a useful insight feed can be challenging with different touch points extending across web, mobile and apps: each with different nuances in capturing customer behaviour. Neglect mobile at your peril! This topic alone could take up a whole blog, for now I will assume that you have this covered and that you can put this data to work. So, what would you use it for?

Tracking and measurement

How do you know if your CX is great? Are customers having trouble with a certain page in their journey or are they showing a preference for certain content? This is the most direct way that behavioural data can impact the customer experience. One of the great advantages of digital is the ease of quantification of online customer actions.


The key to success here is effective tagging to create a direct link between the experience and the outcomes of tracking customer behaviour across touchpoints. Getting the correct taxonomy (including 3rd party tags) in place is crucial to capture their desired customer behaviour.


Coupled with good analysis, this allows the customer journey and your most popular content to be measured and problem areas to be identified.  


Knowing your customer

Key to the success of your customer experience is the capability to respond to individual customer’s intentions. You can only do this if you know who that customer is.

Effective knowledge to capture can be as simple as knowing whether this is a returning customer and what they have looked at previously on a single touchpoint. More difficult is tracking a customer journey across touchpoints.


The best solution is to create a single, overarching marketing ID that links together customer profiles on each of the touchpoints into a single customer view. This ID will allow for much better insight and far better opportunities for creating a tailored experience across the customer journey.

Targeting and segmentation

Targeting the right customers with the right message at the right time is a fundamental principle of effective marketing. Creating segments based on actual customer behaviour can be powerful, as instead of being based on generalised demographic targeting or matching the ‘ideal’ customer profile, the segmentation of customers is based on proven actions.


To implement this effectively, you need to be able to capture customer behaviour throughout the journey and turn it into useful segments that serve a business purpose.


We’re probably all familiar with Spotify’s suggested playlists (rather than their personalised offerings), which are targeted at single users based on that user’s listening behaviour, rather than just demographic data. This creates a ‘sticky’ customer experience that encourages further product usage by matching a customer desire with a tailored answer. This could just as easily be a car company targeting returning website visitors with a homepage that displays the model that they have viewed previously.  


Optimisation

Test, learn and iterate is an oft-repeated mantra of digital organisations. The same approach, a step up from simply measuring behaviour, can be applied to optimise your customer experience: A/B and multivariate testing are becoming increasingly commonplace in splitting customers up to test different elements of experience in a structured way, adopting the most successful and then repeating the process.


There are well documented examples of the direct correlation between successful testing and revenue uplift.  Sony were challenged by low banner ad conversion on their homepage. To solve this they employed A/B testing, pitting different calls to action against one another and measuring their customers’ response.The most successful banner ad optimisation increased conversion by 20%.

Personalisation

The nirvana of data-led marketing is one-to-one personalisation at scale. According to a 2017 Econsultancy measurement and analytics report, 72% of marketers claim it is the most important goal of data-driven marketers.

Using customer’s online behaviour can act as a powerful springboard for personalisation, allowing tailoring based on their interests, previous interactions, messaging seen or stage in the customer journey. The latter can be particularly persuasive in reinforcing previous messaging, highlighting different elements of the message and encouraging additional engagement, creating better business results.


Successful personalisation relies on 3 key capabilities: the ability to share consistent content across channels, the ability to tie customer behaviour into coherent journeys and the intelligence to deliver tailored content depending on a customer’s profile.  

The expectations around customer experience are continually on the rise, so the critical role of the data that powers it will continue to demand more attention from those organisations aiming for success in the future.


With GDPR on the horizon, organisations data gathering activities will be revisited once again and there is no better time to make sure that your data and analytics is serving your customer experience platform well. Putting data to work is no easy feat. It requires a seamless coupling of understanding who customers are and what they do at one end, with the creation of intelligent, automated and personalised journeys, happening in real time, at the other. And with the current influx of AI solutions - think IBM Watson and Adobe Sensei - there will be more focus on those owning the customer experience to understand customer behaviour and turn that understanding into competitive advantage.