In today’s guest post, Gooroo’s general manager of marketing solutions Andrew Aitken (pictured below) discusses why much of the data being collected today based on applied demographics only gives half the story, and provides advice on how marketers can make better sense of their existing data.
Mention the word ‘data’ to a marketer and you’ll probably notice an obvious physical response – a twitch, an eye roll, a scoff, tearing out hair, maybe a whimper. Over the past decade, marketing departments have become depositories for all types of business and customer data – CSAT results, customer surveys, purchase trends, browser trends, social engagement and more – enough to send even the most organised brain into chaos.
The reality for most marketers is they are chasing their tails, bogged down in execution whilst also finding the time and know-how to make sense of ALL THAT DATA, all the time. Let’s face it, not many marketers are data scientists, so they rely on marketing analytics to tell them what’s going on. The problem is that analytics doesn’t always translate into results, so the data chaos ensues.
Thankfully, it is possible to make better sense of your data and ensure it can be used for maximum impact. First, it’s important to understand what’s not working.
Some data doesn’t give the full story
Applied demography is an approach to research that is geographic based. It is useful in marketing because it links products and services to consumers who have particular wants and needs, pinpointing the ‘who’ and ‘where’ so companies can tailor their products and outreach to an engaged audience.
However, issues arise when this is the only type of data being collected, because understanding wants and needs statically only gives a company half the story, leading to mistakes that cost time, money, relationships, even entire companies.
The recent case of failed online retailer Shoes of Prey demonstrates the problem clearly. Early on, Shoes of Prey’s net promoter scores told them that customers loved their product. After great initial success, they conducted market research to ask customers if they thought their product should be delivered to the mass market, which was met with a resounding ‘yes’. But when the company delivered, the mass market didn’t buy.
CEO, Michael Fox, admirably admitted its market research didn’t reveal what the consumer really wanted, which was to be shown what to wear and have the work done for them rather than ‘building their own’ product. The data simply didn’t reveal all the information they needed to make an informed decision. Early adopters and natural enthusiasts toward personalisation weren’t a reliable source to be judging the mass market. If you want to know what the mass market thinks, ask them.
The intention and behaviour mismatch
What the data also failed to account for was the fact that what customers say doesn’t always correlate with how they’ll behave in the future. Think how many times in the past week you’ve not done what you intended? You planned to eat lots of veggies and less sugar, but walking down the temptation aisle at Coles you decided you actually didn’t care that much and threw a chocolate bar in the trolley. Human intent and decisions are rarely perfectly aligned.
Data that tells you how your customers make decisions
What marketers really need in order to make sense of their existing data is to understand how their customers make choices, placing what they already know in the context of future behaviour.
Gooroo’s approach to data is built around sociographics, which seeks to understand the individual and the way they approach their decision making. Whether or not they believe in something, or live in a certain location, all contributes to how they go about making up their mind. While they might browse a product, or say they want something, we look at all the factors impacting their choices.
Gooroo’s platform can bring together any human data set assets, analyse them to find relationships, and produce clusters of thinking which show the different approaches to decision making for different customer segments. This type of data analysis helps organisations find clear answers to ‘What is the mindset of the customer?’, ‘What motivates them to buy’ and ‘How do I best communicate with them?’ This leads to smarter product development and user experience, more targeted and meaningful communications, improved retention strategies and ongoing data enrichment.
For marketers, data is essential, but it needs to be predictive in nature. Don’t get weighed down in data that only tells you half the story.
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