Failure to relay data will leave customers with blanket recommendations that are of little relevance to them
In the Dark Ages (circa 20 yrs ago in the Middle East and 65 yrs ago in the US), it was commonplace to walk into your local grocer and be served by the same shopkeeper. He 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 personalized 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 store owner has turned his local grocery into a massive supermarket. And now 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 Superstore has a surplus of and is keen to sell.
In moving to this model of commerce, the shopkeeper has sacrificed the user experience element in order to drive scale and revenue with a 1-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 1 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 core 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 our Supermarket now collects can be very useful in returning the personalized interaction that customers have. However, if the store does not 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.
In the Dark Ages store that contained only 50 products provides more personaliszed, 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 (NASDAQ:GOOGL)research has recently shown that although many people research products online, much of the volume of retail sales still happen in brick and mortar 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 a data management platform. 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 (digital management platform) is an integral component to brands’ understanding, analysis and usage of any data possessed.
The Drum, a British trade magazine, predicts that by Y 2018 over 90% 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 3rd-party behavioral data and environmental data) into 1 central place. It is then used for audience segmentation, improved personalization, cross-device targeting and predictive analytics, to name just a few.
But, if left to itself, 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 1st-party data.
To go back to our Dark Age grocer, then he knew his customers habits, he knew what they liked and did not like and made recommendations or offered assistance based on this, this was his 1st-party data.
Nowadays, the modern grocer still has this data, now collected via online behavior, cookies and device IDs, but is just 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.
Here are 3 Key ways for to leverage the data a retailer collects in forging stronger relationships with the consumers, as follows:
- Personalization is essential and must come from data. Today’s audiences demand personalization as a standard, a 2015 Microsoft (NASDAQ:MSFT) study revealed that 48% 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 consumers online behavior is trackable, meaning that brands know a great deal about a consumer by the time spent their digital shop. They know your demographic profile, your most recent online browsing habits and what products you are currently shopping for. Imagine you gave your Dark Age grocer all this information face to face and he still offered you something completely irrelevant, you would be pretty annoyed, yes? So why would this be acceptable for online advertising?
- According to the Criteo 2015 State of Mobile Commerce Report, nearly 40% of transactions occurred across multiple transactions in Q-4 of Y 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 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.
- It is one thing to deliver a personalized 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 1st, 2nd- and 3rd-party data can help to 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.
So, 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, now 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.
By David Barnes
Paul Ebeling, Editor
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