When VisualDNA profiled Mindshare at #mshuddle #infographic

Girls love Google, Boys love BBC, why Richard Branson may have had an imaginary friend and a new face for Android. What VisualDNA learned when we profiled Mindshare’s Huddle #mshuddle

Above: The VisualDNA team (in lab coats) at Mindshare Huddle

Last week myself and two other members of the media team, Ed Weatherall & Kristen Anderson, attended Mindshare’s annual Huddle. I’d not been before and wasn’t sure what to expect from an ‘unconference’. Intended as a departure from the dry presentations you tend to get at regular conferences, we came up with the idea of creating a psychologists’ office where we’d psychoanalyze people using one of our quizzes. [Read more…]

Infographic – how VisualDNA creates emotive data from quizzes


Can marketers get more personal with data without personal data?

This article first appeared in The Guardian on 30 August 2013.

By Ian Woolley, Chief Commercial Officer of VisualDNA

Marketing changed forever with the dawn of the digital age. As endless streams of consumer data flowed across the web into the caches of the emerging data companies, their insight into purchaser demographics were significantly enriched. Although it has taken the best part of a decade for digital marketers and data professionals to develop a means of effectively cultivating useful insights from this data, we’ve now hit a point where marketers are, on the whole, good at getting data and using it effectively within a digital marketing strategy.

But as the digital landscape constantly changes, new services, technologies and devices enable previously uncharted routes to conversion. These new tools and technologies are making marketing increasingly complex. Better ways of collecting data and generating insight are required if today’s digital marketers aren’t to find themselves at a dead end.

Digital marketers mustn’t forget that the consumer knows they’re being watched data horror stories increasingly pop up in the press and consistent government warnings, snooping scandals and safety campaigns mean virtually every single online shopper is now aware that their data is being collected and used in some capacity.

This is undoubtedly a good thing. Despite the general public reaction of mild hostility, many of us now expect our data to be turned into a better, more relevant internet experience, whether that’s suggested products, customised content or targeted ads. Personalisation is king.

But the current status-quo of data collection is incapable of meeting such a demand. With the exception of Google, Facebook and some of the world’s biggest publishers and retailers, few businesses are able to anticipate the needs of the person behind the cookie. And third-party data only goes so far. Segments built on age, sex, race and income help create a picture but simply can’t provide digital marketers with the emotional and psychological characteristics they use to define their customers. How can you personalise effectively if you don’t know the person?

It’s evident that better personalisation means better conversions. I’ll give you an example. Last week I got a text message from EE (Orange Wednesdays) asking if I enjoyed the film last week. While that campaign has been a hit by anyone’s standards, I’d prefer it if they could deliver more helpful suggestions.

Emotive data  insights into an individual’s attitudes towards love, finance and movie taste, for instance could make that possible. EE could send a suggestion of booking a 2-for-1 deal on the upcoming love story for a financially conscientious romantic or a Friday night comedy for a fun lover. This insight helps a digital marketer turn what could be construed as a spam text into a personalised and relevant communication.

Digital marketers are seeking out data-derived insights that help them to connect with people on an emotional-psychological level, because only with deeper understandings that address emotional characteristics can marketers deliver a personalised experience relevant to each individual’s needs. But this needs to be balanced out with consumers’ growing concerns about how their data is collected and used. Fundamentally, the eventual answer lies in people owning their own data, a concept called vendor relationship management and using it in a way that delivers them value. However the technology, consumer demand and business models for such an undertaking are yet to emerge, leaving big data (owned by businesses) as king.

Until then, perhaps emotive segments are the best way to deliver a personalised experience without personal data.

Emotive Audience Segmentation: The Science Bit

At VisualDNA we’ve developed a patented way of uncovering a person’s needs, their desires,  and the things that are important to them.

We start by promoting free visual personality and lifestyle quizzes that give users insightful and astonishingly accurate feedback about themselves.

This is especially true with our newest, most advanced quiz, Who am I?, which classifies people according to the Big 5 factor theory of personality: openness, conscientiousness, extraversion, agreeableness and neuroticism.

The process of turning the results of a visual quiz into a rich, accurate online audience profile isn’t completely seamless or straightforward.

Making sense of terabytes of quiz data and scaling the solution out to a global audience network is as complex as the personalities of the people who take our quizzes.

In fact it’s far too complex to go into in a blog post. So, we asked our team of data scientists, creative developers and psychologists to sit down and tell us how they do it, and put it all in a white paper.

  • Why do we use image rather than text-based quizzes?

  • How do we extract meaning and understanding from the full response pattern of a user?

  • What kind of algorithms and mathematical formulae do we use? (the real science bit)

If you’re asking yourself any of these questions, then we think we’ve got the answers for you.