Barry Smith, Senior Consultant at retail loyalty specialist Ikano Insight takes a look at Big Data, the market buzzword of the moment.
Article from Cabinet Maker issue 28 February 2014
Last year was the year that retailers were lectured by data experts on the importance of Big Data, but not many retailers managed to harness it properly and integrate it into their businesses. This year those retailers that employ Big Data effectively to steer their business and marketing objectives will in my opinion offer themselves a competitive advantage. Or, to put in another way - if they don’t they will get left behind.
Big Data with its trillions of bytes of information available can be a significant issue for retailers. Large, unstructured complex datasets such as text, images and video from websites, social media, smartphones and tablets can be difficult for retailers to capture and use. Even if it could be captured how should retailers use it? Does it link to and further their relationships with customers more? Will it boost their profits?
Global data volumes are predicted to grow by 40% each year according to McKinsey. So for me, those retailers that get board buy-in to the power of Big Data now, and begin building the appropriate systems and relationships in order to use it to make the complex simple, will be able to put a true value on the engagement and profitability of each customer.
The good news is that it’s not as difficult as lots of data experts might lead people to believe. Retail businesses will have already determined their key marketing objectives, which are usually a variation on increasing customer spend, increasing frequency and reducing attrition. All retailers need to do now is consider which data is essential, what data to use now and also think about what data they could get access to. If the data is not going to support a retailer’s objectives and doesn’t help them grow their business, then why bother to collect it?
Retailers by the very nature of their businesses are data rich and have a massive potential for using Big Data. They have the ability to link their customers to their transactions (e.g. by using a loyalty or reward programme), in stores and online, and through their engagement using social media and customer services. This means that they can then find out how often customers are buying, how much they are spending, when they last spent, what products they buy and their preferred channels.
This information also allows retailers to understand the relationship between customer engagement and profitability, as opposed to just collecting ‘likes’ on Facebook!
Imagine if retailers could know that their most valuable customers in terms of spend and loyalty are standing instore, and that they could deliver them communications to their smartphones in real-time to protect and defend them against competition. This could be achieved by surprising or delighting them in real-time. It could also work for a lower value customer who might usually spend £20 per visit - with the retailer being in a position to deliver an incentive that will stretch them to a £40 spend whilst in store. Of course the beauty of data is that it can test outcomes, with retailers finessing their approach as they go along.
As mentioned earlier, it’s important to make sure that retailers are clear on what data is required to deliver actionable insight. I think it’s important not overthink things and automate where possible but make sure that controls are in place to enable performance to be measured properly. Delivering automated recommendations to customers based on previous purchases shouldn’t just be the domain of Amazon. This approach offers retailers a truly linked online and offline approach. Retailers need to remember their marketing basics, i.e. what are they trying to get the customer to do? Is it to spend more per transaction by cross selling or giving stretch targets, spending more frequently or simply stopping customers from leaving by offering incentive deadlines. If the data doesn’t deliver, get rid of it.
Customers are now readily leaving retailers data footprints such as social media and website interaction as well as geolocation data in mobile apps. A fuller picture of customers using this information is just as important and predictive as transactional data to determine engagement levels, segmentation and the potential profitability of customers. The two combined is even more powerful. We can now integrate with retail EPOS data and capture and build into our segmentation strategy the way customers engage and feel about a brand and how that affects profitability.
The challenge for lots of retailers is that they feel they are not experts in this space of Big Data management. There are a number of decisions that will need to be made, e.g. should they look to do things themselves, use an expert third party or a combination of both? If they wish to handle the project themselves they will need the means to capture critical data, making sure they gain the secure permissions and trust as well as ensuring they have a true single customer view at the heart of everything they do. Once retailers have this single customer view, they will be able to understand which segments are worth marketing investment, what offers will be able to drive customer behaviour and how to personalise their communications accordingly.
Considerations need to be given in terms of collecting, loading and processing vast amounts of data in flexible data formats so it can be indexed for easier searching and referencing. Cloud services are now the norm when considering solutions for collecting Big Data, but they must be able to cope with the volume, variety and speed of both collection and actionability to deliver on the insight.
Better tools and greater knowledge about how to apply Big Data concepts mean that the retail landscape is changing rapidly. Retailers that are able to integrate Big Data by removing data silos and creating more efficient ways to connect the customer journey will deliver incremental gains over the next few years.