There’s no getting away from the fact that the current economic environment is among the most volatile in living memory
By Natalie Cramp is CEO of data science company Profusion. Profusion is a leading provider of data and marketing services, ranging from consultancy advice, through to the creation and execution of innovation projects and marketing campaigns.
We’re all beset by a host of unknowns that makes any long, or even medium term, business planning incredibly difficult. However, while it can be easy to dwell on the challenges and uncertainties, there are a lot of ways businesses can take control of their own destiny. Chief among these approaches is truly understanding customers to anticipate and meet their needs.
On the face of it, understanding your customers may seem to be the most basic piece of advice. Indeed, I would imagine nearly every business owner would say they know exactly who their customers are and what they want. Therein lies the problem. Many businesses are so certain they know enough about their customer base that they can become complacent.
Customers are a dynamic bunch. This means, not only does their data often quickly become out-of-date, it also means that the mechanisms a company uses to collect information or even the data points themselves can become obsolete. Businesses that believe they have robust data capture and analysis processes can be lulled into a false sense of security. Those that don’t even undertake customer data analysis and instead rely on gut feel are essentially groping around in the dark. These problems can be masked by a buoyant economy. It is only when the real challenges hit do many companies realise how little they know about their customers and are left simply guessing about the best way to respond.
Thankfully – it is never too late to fix the problem. The first step is recognising you can do more to understand your customer base. Next, is making a simple but effective plan to learn more.
To do this, we need to reveal what we do and don’t know about our customers. For companies with marketing or sales strategies already fueled by customer data, this means examining performance over the past few months. Questions such as, were you able to identify vulnerable customers to provide them with additional services? Could you tell if someone had been furloughed? Do you know if your online customers were people that previously went in store? Are they new? How has their purchasing behaviour changed? Has something significant happened in their life lately that could change that e.g. buying a house or having a baby? The list can go on and on. If the answer to these questions is ‘no’ or ‘we’re not sure’, chances are your business might have a lot of data but little of it is providing the insights you need.
After you’ve identified what you do and don’t know about your customers, the next step is to clarify what you need to know. Often the best way is to work backwards from the essential questions you need answers to. For example, have my customers churned or simply deferred purchases? Are they spending less or buying different products? Whatever questions you believe will provide you with the information you need to make major business decisions are the ones to zero in on. From there you can identify the data points and analysis you need to undertake.
We then come to the seemingly tricky part. How do we collect and analyse this data?
The most effective strategy will differ between businesses, however, there are some basic principles that apply in nearly every situation. First and foremost, trust is key. Businesses need to approach data collection in a transparent and ethical way. Attempting to dupe customers into sharing more information than they want to or misleading them on how you intend to use their data is a surefire way to wreck your brand. Consequently, only collect what you need and in a way in which it can be effectively used. Remember, data science can be a powerful tool for filling in the blanks. By analysing customer behaviour, certain information can be inferred with a reasonable degree of certainty. For example, purchasing pattern or marketing engagement changes that indicate a customer has changed jobs or may have a child on the way.
The critical thing to remember is you don’t have to get bogged down in complexity. In our experience, a surprisingly large number of companies simply fail to ask their customers questions in a direct way. This may be due to fear of alienating them or the perception that few will readily provide information. In reality, many people are willing to part with personal information if they understand that it will result in a clear benefit to them. Articulating how their data is used and what they get out of it is incredibly effective. Of course, restrictions still do apply. When and through which channel you seek to ask your questions will depend on each person’s individual preferences. There will also be limits on how many questions you can ask over a particular time frame. Using data science to first work out the type of question which will glean the most useful information and then testing your customer base to ascertain the most effective strategy for asking them questions is an absolute must.
Another misconception is that data science or even basic analysis is beyond the resources or expertise of all but the largest businesses. This is simply not true. There is plenty of support available out there at a competitive price. There is also a huge trove of resources freely available online that will help businesses upskill themselves and their workforce. Ideally, nearly every member of staff should have some rudimentary data analysis skills – that’s worth investing in. For the smallest businesses, even the most simplistic analysis of customer data to uncover insights will be bettwe than nothing.
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