How data can help retailers improve customer experiences

Failure to relay data will leave customers with blanket recommendations that are of little relevance to them



In the dark ages (circa 20 years ago), it was commonplace to walk into your local baqala and be served by the same shopkeeper (let’s call him Saif). Saif always welcomed you with a smile, knew your habits and preferences, made useful suggestions of products that you may like, and even offered to help you with your selection. This provided everyone with a personalised shopping experience and a relationship with the shop that was warm, useful and over time, meaningful.

Fast forward 20 years and though consumers’ purchasing habits and channels have changed, their experience expectations have not. Our local baqala store owner, Saif, has turned his local grocery into a massive supermarket. Rather than greeting you with a smile at the entry, someone asks to see your bag before stapling it shut, and you’re offered at best, half-hearted suggestions based on what Saif’s Superstore has a surplus of and is keen to shift. In moving to this model of commerce, Saif has sacrificed the user experience element in order to drive scale and revenue with a one-size-fits-all approach.

This story rings all too true for the online advertising industry, where consumers have been shifted from an experience-oriented world to one where they are bombarded with irrelevant messages. Consumers are overwhelmed by brands attempting to sell them just about anything, all because they fell into a bucket that someone once created. Messages have become both indiscriminate and impersonal. At the crux of the issue is data, and particularly actionable data, or the lack of it. The industry has formed tunnel vision around ‘big data’, often at the expense of actionable data. Think of the data here in terms of consumers’ recent browsing habits, new product information and the shop’s stock levels.

The ‘big data’ that Saif’s Supermarket now collects can be incredibly useful in returning the personalised interaction that customers have. However, if the store doesn’t relay this information to its staff or just provides snippets of it, the effect is lost and customers will continue to be offered blanket recommendations that are of little relevance to them. Herein lies the difference between big and actionable data. Saif’s previous store that contained only 50 products provides more personalised, relevant experiences and therefore gets your repeat business since it is agile enough to truly act upon whatever amount of data it collects on you, proving that bigger is not always better.

Another misconception in the industry is that we tend to refer to data entirely as an online commodity. Google research has recently shown that although many people research products online, approximately 95 per cent of retail sales still happen in physical stores. There is a host of vital data to which we are not currently privy and therefore cannot include in our strategic planning and optimizations. Again, this is information housed within the big data umbrella, sitting in an entirely unusable capacity. This data will be productive when we can use and combine it with the information in our data management platform (DMP). This is when we will be able to assess the impact of online advertising on offline sales or build online models and audiences based on offline behaviors.

The DMP is an integral component to brands’ understanding, analysis and usage of any data they possess. The Drum, a British trade magazine, predicts that by 2018 over 90 per cent of brands will use one. When implemented and utilized correctly, a DMP will ingest raw data from a wide range of sources (from a brand’s own data to third-party behavioral data and environmental data) into one central place. It is then used for audience segmentation, improved personalization, cross-device targeting and predictive analytics, to name just a few. However, if left on its own, a DMP will do little more than appear on a slide in an agency’s pitch deck.

The fact is that most brands already have the data that will improve their consumers’ experiences and generate new ones; it’s called first-party data. To go back to Saif, 20 years ago he knew his customers habits, he knew what they liked and didn’t like and made recommendations or offered assistance based on this – this was his first-party data. Nowadays, the modern Saif still has this data (now collected via online behavior, cookies and device IDs), but is simply not making use of it. Effectively, the shopkeeper knows you hate fish but continues to offer you the catch of the day regardless. Unfortunately, this is the reality for many major businesses today.

On the other hand, if you already utilise a DMP, what more can you do to make your data actionable? Here are three key ways for you to leverage the data you collect in forging stronger relationships with your consumers. Firstly, personalization is absolutely essential and must come from data. Today’s audiences demand personalization as a standard: a 2015 Microsoft study revealed that 48 per cent of customers expect brands to know them and help them discover new products that fit their needs. It is no secret that a lot of our online behavior is trackable, meaning that brands know a great deal about you by the time you come to their digital shop. They should know your demographic profile, your most recent online browsing habits and what products you are currently shopping for. Imagine you gave Saif all this information face to face and he still offered you something completely irrelevant; you would be pretty annoyed, no? So why would this be acceptable for online advertising?

According to the Criteo 2015 State of Mobile Commerce Report, nearly 40 per cent of transactions occurred across multiple transactions in Q4 2015. We must use the data within our DMP to move beyond looking at each device individually and reach a place where we can speak to our customers at a user level. Imagine having a detailed conversation with Saif in the morning about what product you want to buy, only to return in the evening wearing a different shirt and having to start the conversation all over again. Once again, actionable data must play a part here to help us match customers to their devices.

Finally, it is one thing to deliver a personalised experience to a returning consumer, but anticipating in real time what new consumers want before they go shopping is so much more powerful. A DMP that houses first-, second- and third-party data can help us achieve this with predictive analytics. Through actionable data, we can develop models through an amalgamation of onsite and offsite behavior to offer content to customers before they are actively in market.

When you think about your approach to data, just remember – which store would you rather visit? The superstore store with a million products that are impossible to find, or the small store round-the-corner that offers you the right product at the right time, adapted especially for you? Of course, you can have both, and in time we must, but for now let’s focus on getting the shop in order with the help of actionable data. The future belongs to those who can combine a wealth of products, relevant context and cognitive learnings in order to fulfill the personal and relevant experiences that consumers rightfully demand.

David Barnes is Associate Director – Digital Data at PHD UAE