The ever-growing volume of customer data available presents a really exciting opportunity for marketers and insight leaders to become even more valuable to businesses. They are the strategic drivers, providing the insight that helps determine new business models and strategies.
But putting this data to good use isn’t without its challenges. Whether it’s website, social or loyalty programme data, using it to engage with customers at the multiple touchpoints on their journey has become a much more complex proposition. We all know data can help deepen our relationships with customers, but we don’t always know the best way to go about it.
In truth, it’s not just about data. It’s discovering the stories within it, relating them back to the customer journey and turning that insight into action that really makes a difference. In our work with our clients, we’ve found four key ways to successfully leverage customer analytics and see beyond the data:
1. Think strategically, act tactically
The pace of change in marketing is such that we can no longer justify spending six months figuring out how to improve the customer experience. It’s now about creating small, incremental improvements to specific areas. To do this, it’s important to look at the bigger picture and analyse a variety of datasets. Sales data is interesting, but if you combine it with loyalty scheme and social media data – and find relationships and insights within those sets – then it becomes significantly more valuable.
2. Get to grips with the customer journey
Increasing sales isn’t always the end goal. Things like retention and shedding costly customers can be just as important. The first step is to define the most important element of the customer journey for you – and that might not be conversion.
IBM customer Clear Returns uses customer analytics to help retailers minimise the negative impact of returned items. The sale is not made when the goods are shipped, but when the customer keeps them. Clear Returns helps companies use data to understand their customers – and gauge the likelihood of products being returned. Interrogating a wide selection of data at this point ensures that retailers can make timely interventions that ultimately lower return rates – and, crucially, improves customer satisfaction.
3. Find the story in the data
Once you have your dataset, find the story that makes the difference. To do this, you need to combine your knowledge of the business with your skills in interacting with the data. A common mistake when interrogating customer analytics is arriving at the data with preconceived notions of what you’re going to find and attempting to manipulate the data to support that. Moving from being intuition-driven to being data driven will be a step change for many marketers, but if you listen to the data you’ll reap the benefits.
4. Share your story
The final – and most important – step is to share your story. Find an analytics tool that helps you pull in data from a wide range of sources, refine it and drill down to extract meaningful insights in an easily accessible and shareable way. Then distribute your insights throughout your company and use it to make changes to your operations.
If you’re interested in discovering a new way to work with customer data using IBM’s Watson Analytics, you might like to register for our free event on 1 April at the Royal Institution in London.