Matthew Ashford, director of analytics at Gobeyond Partners, explains how SMEs can use their data and analytics to generate actionable insights
SMEs may have limited budgets available to invest in data scientists and expensive analytics tools, and as a result they will need to find innovative ways to generate actionable insights from the customer data and tools they already have at their disposal.
First off, and most importantly, they will need to use customer data in a responsible and compliant manner. All businesses (no matter their size) will need to understand their obligations under GDPR and ensure that they have the correct customer permissions in place.
In terms of capturing and analysing feedback from customers about their perception of the products, services and overall experience, businesses can gather this insight in a number of ways. For instance, they could conduct surveys, capture comments made about the business on social media and review sites, collate insight from conversations (such as call listening, speech and text analytics) and, of course, use feedback from frontline staff too. Saying this however, one of the key challenges that businesses tend to face is joining up all this data they have generated. To create a single customer view across a website, CRM, and across various sales and service channels, businesses will need to have a single customer identifier across all channels. Many organisations have gaps in this ecosystem, so the art of “fuzzy joining” becomes important. This is where we might use a time stamp or some other data item to make a reasonable assumption that a particular interaction was probably customer x, even where the absence of a unique customer identifier prevents us from knowing this for sure.
To further understand customer behaviours, they can look for patterns in their customer data that will help to identify how their valuable customers behave, vs those that maybe purchase once and then don’t return or even prospects who have registered their details but failed to complete their purchase.
They can use this insight to improve and individualise customer journeys to turn lower value customers into higher value ones and retain those that already contribute the greatest value to their business.
On the topic of customer data, it’s important to note that some of the most valuable data is unstructured. We routinely find that an organisation’s contact dispositioning data, (the reason codes for people’s calls) is simply not detailed enough to create a meaningful picture of how the customer is really experiencing the journey that has been ‘designed’ for them. By using unsupervised machine learning techniques (such as text analytics), we can uncover the hidden breaks in the journeys. We can the link that data to other sources, to quantify the contribution each break is making to customer satisfaction or sales attrition. For example, with a recent client we learned from text analytics that customers were calling about the sizing of certain high-price products, which helped us discover that the sizing guide was inaccessible on the company’s website. This created an opportunity to reduce inbound contacts and to reduce customer effort, but also to prevent revenue leakage by enabling more customers to proceed with their purchase rather than going to a competitor. Interestingly none of this was already being taken care of because the internal list of call reasons didn’t include sizing as an option.
Once we’ve used these techniques to bring the journeys up to a good level of hygiene, we can move toward a new level of personalisation by offering customers bespoke deals and options that work well for them based on their buying history. It’s little things like this that help change a one-off engagement into a long-term loyal customer and brand advocate.
Certainly, exploiting the power of customer analytics needn’t be complex or expensive to make a real difference. Armed with actionable insights from listening to customers and understanding their behaviour, it’s very possible, affordable and relatively straightforward to develop customer experience for a business that really gets to the heart of what customers need and want. In short, and contrary to popular belief, firms of all sizes can make use of customer experience analytics so long as they carefully and legitimately collect the right data and then interrogate and utilise it correctly. It really needn’t just be for big business.