In a traditional attended sales process, you don’t need to guess how your customer is feeling. Your sales people, if they’re on the ball, will know. But what about an automated sales-pipeline? You’ve constructed your personas, tested your theories, and targeted your copy. But how can you tell how your customers feel about it all? Your data is your friend.
The most obvious way to use big data to understand your customer journey is the one we’re all familiar with: by looking at the metrics from your sales pipeline to understand where the bottle necks, pain points, and leaks are.
"Many companies, even some fairly sizeable ones, don’t appreciate just how much even their transactional data can reveal about the way their customers feel", says director and data specialist Paula Atherill of the company Creative Analysis. "With a properly mapped customer journey and the right tools, you can go a long way toward getting a very nuanced understanding of your customers emotional response to your brand and your customer journey".
By analysing metrics such as your traffic drivers and your on-site search data, you can quickly build a picture of what your customers are looking for. Match this data to the points at which customers exit your sales pipeline, and whether or not those exits were converting or non-converting, and you build a picture of the parts of the customer journey that are working and those that are frustrating your customers.
That’s a good start. And, frankly, a lot of companies still aren’t doing it. But is it possible to go further? Can you use data to understand the personalities behind your customer segmentation profiles and then build an experience customised to provide each of those segments with exactly the right emotional triggers to prompt conversion?
The holy grail of marketing
It sounds like the holy grail of marketing. But sentiment analysis is already changing the way brands work. By analysing large data sets generated through spontaneous user actions, for instance product reviews or social-media posts, it’s possible to identify customers’ attitudes and emotions towards a specific brand, product, or other variable.
Although still necessarily crude in some respects – detecting sarcasm on Twitter, for instance – sentiment analysis already allows companies to find better ways to interact with customers, manage their brand’s image and improve their marketing. The most forward-thinking brands, are now also applying sentiment analysis to their customer journey.
Tools are now available that allow companies to collect data in real-time from online reviews, chat applications, social media, and even call-centre conversations. This data can be analysed both in real-time, to identify changing moods and events to which the company should respond, and in aggregate to find longer-term trends.
By understanding how your customers spontaneously express their emotions at each point in the customer journey, you can move beyond metrics such as the net promoter score to gain a detailed understanding of where your customer journey delivers a good experience.