Keeping customers happy is crucial to any business. Happy customers rate you highly online, they tweet about their experience and most importantly, they come back.

However, in a world driven by clickthrough-counts and loosely correlated stats, gauging how happy your customers are and utilising that soft data is much harder than it seems. Nimbus Ninety members gathered in the Covent Garden Hotel to discuss not only how to achieve the perfect happiness rating, but also how to measure it.

Too much noise

You would think that one of the hindrances to understanding the customer is not having enough data about them. In fact, it's the opposite: businesses have far more data on their customers than they know what to do with. The challenge is learning how to manage and utilise that data effectively.

With every interaction, customers give more of their data to businesses. Business and customers today have reached an understanding of the value exchange. Customers give data on the prerequisite that the service they’re receiving will somehow improve. “Tell us your favourite store” has the subtext of “because we want to give you a discount on your next visit”, with the understanding that both the customer and the business will benefit from the exchange.

Or at least in an ideal world, it should.

Part of getting this interaction right is cutting through the noise of too much big data and getting to the qualitative understanding of your customers. One member mentioned not maximising the analysis of the marketing data that was coming in: analysis only happened on transactional data. So much of getting the right data is about nailing the moment you ask for it. If you create an experience for a customer, you have to give them 4 or 5 quick questions about their experience right away. We live in a world of short-term memory spans, and customers will have forgotten and moved on to the next thing by the time a survey comes a day later. Collecting real-time qualitative data on customer experience is crucial.

Another member talked about “data silos” impacting his organisation, with data being collected from all sorts of places. Ensuring the data is both connected to each other and maximised through analysis requires navigating the tension between data silos and the drive to be a “data-driven business”. Collecting this data in a connected way requires implementing systems that have the ability to integrate with each other: creating the push for this needs persuasion of senior stakeholders that this is in fact necessary for business growth.

A digital relationship

Collecting digital feedback of interaction with a brand can take many forms. Some members used email surveys and some did regular audits of social media.

However, one point that came out consistently in conversation was the need for humans to interact with other humans. A chatbot just won’t do when a customer has had a bad experience and needs the organisation to fix it. Similarly, customers have a tendency to only leave reviews online or interact with customer services if the experience has been truly excellent or utterly terrible. Collecting this data skews the average with its extremities.

Indeed, the end goal of collecting all this data, much of which is collected incidentally just by interacting with the customer, is to gain actionable insights to improve the experience of customers. Data analysis that is not statistically robust, that jumps to loose correlations for the sake of reaching one, creates poor and inaccurate insights.

As retail migrates further online and away from the high street, creating the online customer experience is needed to drive online sales higher. A feedback platform that can cut through this noise of too much feedback data is necessary to achieve the seamless and intuitive customer experience - and therefore, customer happiness.

This event was in partnership with Usabilla, a feedback platform that helps brands become truly customer-centric by improving digital experiences.