How data can reveal customer behaviour changes
As lockdowns lift in the UK, we’re all moving from ‘unprecedented times’ to the ‘new normal’. However, what the full implications of this new normal are and just how long they will last is anyone's guess.
Many retailers are moving from the relative, albeit painful certainty, of being told to shut to the uncertainty of being allowed to open if they follow stringent guidelines. As the rules differ across industries and the timing and policies regarding openings are in a constant state of flux, many retailers can rightly feel their new normal is a state of confusion and complexity. There are simply a lot of unanswered questions. The biggest unknown facing retailers is how will consumers react to the easing of lockdown.
Although the first week of non-essential retailers being allowed to open saw queues for some businesses over a mile long, we’re still in the dark about whether there has been a significant bounce back. Has consumer demand being permanently depressed? Have people deferred purchases they would have made during lockdown and are now making up for lost time? Has there been a more permanent switch to online and bigger retailers? Are people spending more due to savings made during the lockdown?
The answer is unlikely to be clear for many months and even then it will impact each retailer differently. There will also be the added unknowns of how the reopening of the hospitality and travel sectors will impact spending patterns. By the time the picture becomes clear it will have been too late for many retailers to have adapted their strategy. Consequently, retailers need to take control of the situation by having a proactive strategy underpinned by data.
The exact approach will vary markedly between businesses, however, there are some steps that every retailer can take that will help them develop a response:
1) Identify your data assets and gaps: Website analytics, sales data, marketing and social media engagement stats etc. are available to nearly every business and will provide the bedrock for understanding how conditions have changed and (most importantly) could change in the future. If you don’t currently collect this data, it is absolutely critical to set up processes that will store it in a manner in which it can be easily analysed.
Often the biggest knowledge gap retailers have is in store. Beyond simple transaction data, retailers are blind to footfall, customer journeys around the store, connecting in store customers with online identities, how and why sales are abandoned and the general sentiment of customers. This data dearth can manifest itself in low marketing engagement stats, inaccurate predictive modelling for sales and, most visibly, an inability to answer simple questions - for example, ‘which of my customers are vulnerable?’.
2) Decide what questions you need to answer: Not all data points are created equal, nor is it practical or wise to attempt to collect everything you can - it is a pointless and time consuming exercise. The best approach is to first think about the questions you want and need answers to now. For example, how does in store footfall compare to pre-lockdown? How many customers are not making purchases due to queues because of restrictions? Are the in store customers new or online customers that prefer to now shop in physical locations? From your list of questions you’ll be able to work with your data specialists to determine the exact data points you need and therefore what new information you need to collect.
3) Keep your plan simple: Businesses can often get bogged down in complexity. Companies often approach data collection with a near fatal misconception that customers need to be duped into providing their data. The reality is that many people are happy to provide information directly if they approached in a transparent manner and can see the clear benefit of doing so. Asking customers questions via in store surveys or online polls is often the most effective strategy. With conditions as they are, most will understand why you would need to know their thoughts and feelings. For information that can’t be easily obtained by direct questioning or observations from your in store staff (e.g. on footfall), technology can provide assistance. One example is using fintech software that captures and collates card data from purchases, helping you to link in store and online identities.
4) Analyse the data - quickly: The depth to which a business analyses data is of course dependent on their resources. There will also be large variations in the approach that will work best - updating existing models, creating new algorithms, looking at how data is integrated into existing enterprise software and Business Intelligence platforms etc.. However, with the retail environment likely to be highly volatile, the key will be to ensure that the insights gained are updated as regularly as possible - ideally in real time. It is also worth noting that getting assistance from data scientists isn’t as expensive or daunting as it sounds. Often they can work with a business to quickly set up the models that are needed and, with the right data architecture in place, they can, with a little training, be run by any member of staff to continually provide insights.
5) Include and educate your team: There is little point in having a lot of data or insights if they cannot be acted upon. Every team member across your business needs to know why data is collected, what it does and doesn’t tell them and what the insights really mean. The more people you have reviewing and understanding the data the more ideas your team will generate and the faster your business can respond.
6) Test, learn and adapt: A scientific approach can help to mitigate risk and light the way forward. This is a perfect time to test new strategies. If, for example, you’re presented with data that in-store sales conversions are very low, you can test different solutions to identify which is the most effective.
This is of course just one route to collecting, analysing and using data that can help retailers make better decisions. If this sounds daunting to you or simply beyond your capability or resources, do not despair. Any information you can collect and analyse at even the most basic level will be better than working entirely in the dark. Simply asking your customers directly how their behaviour has changed might give you the vital clues that tell you how you can adjust to survive and thrive in the ‘new normal’.