Let me start off with a confession: In my entire life, I have never used a dating app or a dating website. Of course, I am now a happily married man, but I have been single in the internet era. Yet, I never saw the appeal in meeting women online. (I did develop a very simplistic matchmaker program in computer class in high school, back in the 80s. But that’s a story for another time).
Let me start off with a confession: In my entire life, I have never used a dating app or a dating website. Of course, I am now a happily married man, but I have been single in the internet era. Yet, I never saw the appeal in meeting women online. (I did develop a very simplistic matchmaker program in computer class in high school, back in the 80s. But that’s a story for another time). So to be perfectly honest, I don’t know much about Tinder and match.com or their equivalents, although I certainly don’t judge anyone who has used them. In fact, I find it quite fascinating how quickly we humans adopt new technology whenever it has to do with love (or sex). But the same technology that is used to match men and women (or men and men or women and women), could be exceptionally useful in matching people with brands or products. And that I know a little bit about. My focus is on how we can operationalise the use this type of real-time information in order to make the path to purchase less cluttered and annoying for the individual – and creating stronger connections in a more cost efficient way for the brand.
Data driven marketing is quickly becoming one of the most important tools for targeted communications. And it’s mainly fuelled by Big Data – the aggregation of consumer behaviour. Big Data allows us to see patterns in large groups of people, identify similarities, and extrapolate preferences and behaviours based on this data. It allows us to overlay these data with events, locations, weather, time of day etc. to quite accurately find consumers who are likely to behave in a certain way. It powers a lot of today’s digital platforms, including the global success stories of Amazon, Uber, eBay, Tesla etc. This use of predictive modelling is extremely useful in identifying people who are ready to buy, entering the purchase cycle or are simply in the right frame of mind to discuss the topic or category the brand operates in.
But only focussing on Big Data is a mistake. Even more important is the “Small Data”. Small Data is specific knowledge about individual consumers. It’s not an extrapolation or a prediction, it is real historic and/or real-time data that can be used in specific targeting and in creating personal one-to-one communications. It’s based on specific preferences of that individual – not the “wisdom of crowds”. This is not new, of course, it’s been used in CRM for decades. But with the advent of Big Data, we believe Small Data will have its renaissance. Because when you overlay individual data with aggregated data, you will have the opportunity to predict future behavioural patterns with greater accuracy and stronger personalisation than ever before. It will greatly benefit the consumers, as they will be able to focus their attention on brands, products and stories that are relevant to them, not to their next door neighbour who may be identical from a demographics point of view – yet could be completely different at a more granular level. One’s interest may be in music or art, while the other is more technologically inclined or loves going to bars. Whatever those interests and patterns may be, it is useful to identify these behaviours and preferences, and use them (carefully) in order to establish a closer connection and a better experience for the consumer. The benefit for the brand comes directly from improving the experience for the consumer. It is very tempting to exploit this information in a way that only benefits the brand, but that is a very short term approach.
Instead, think of Big + Small Data as your customer’s best friend. Use it in a way that is unobtrusive and friendly. Let them know you care about their privacy and their right not to be targeted or even talked to. And most importantly, make sure that the communication is interesting, relatable and digestible for them – not just for you, Because as much as we talk about “likeability” as a factor in more traditional brand marketing, being likeable is really about being honest, authentic and trustworthy. Nowhere is that more apparent than in one-to-one communications. Linking people’s expressed interests and preferences with Big Data not only allows them to be put in contact with products and brands that they are interested in, it helps the consumers navigate new products that they themselves would never think about searching for. This is one of the pillars of Digital Transformation, where the culture of digital is at the front and centre of your business model. Being data driven certainly doesn’t mean being cold and computer centric. Quite the opposite. By using these tools, it becomes easier to remain likeable and consumer centric. It’s the first step to actually connecting with your target audience.
Erik Ingvoldstad is the Founder & CEO of Acoustic.
Follow Erik on Twitter @ingvoldSTAR, follow Acoustic at @AcousticGroupSG
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