VisualDNA is working with daily deal providers. Daily Deal sites are on the rise, and today they usually work by emailing the same deals to all users in a certain geographic area, e. East London. VisualDNA allows deal sites to personalise these emails, prioritising the deals that are most likely to be of interest, based on the user's VisualDNA.
Over time, our inference algorithm gets better at predicting the deals based on CTR, and what users like them, like. Users can easily click and see which deals they would have been sent if their VisualDNA wasn't being used. How will your analytics and visualisation tools give the daily deal specialists gain better insights into their audience and customer base?
TE: Our analytics and visualisation allows daily deal providers to see in real-time which audience segments are responding to which campaigns, and use this to fine-tune the kinds of deals they offer to maximise uptake. Deal providers can only work with a certain number of businesses due to the way the distribution system works, and VisualDNA insights can be used to help prioritise the deals people want the most.
Will the new privacy directive have an effect on your business within the EU? The collaborative filter finds the users with most similar profiles that have accessed the site in the last 24 hours, collates the stories that those users have read and recommends these stories back to the user. We also integrate with major Ad Servers to enable publishers to sell impressions of specific audiences to their advertisers.
Can you discuss a use case of how a consumer might interact with VisualDNA initially? Consumers are invited to take a VisualDNA quiz via ads and editorial links on our partners' sites. They answer questions about themselves by choosing from a selection of images, and get feedback on what their choices say about who they are.
They can also get relevant content matched to their VisualDNA, for example the product that we have launched for the LA Times filters the news stories of the day and shows the reader the most relevant articles for them. We've launched quizzes on a wide range of topics including Travel, Dating and Health. Our core Personality quiz consistently proves itself to be the most popular with consumers, which enables us to collect a very rich, broad set of data.
Our philosophy is that we put the user first; we always make sure that they get more than we take. How are you selling this data today? What is your target market in terms of clients? Our clients are both sellers and buyers of data.
Specifically, publishers that wish to increase the value of their inventory and buyers that wish to immerse their brands in highly relevant audiences. We are working with a number of different partners to provide rich data on their users.
We sell the products that create the data and often ring-fence that data for the partner, but this depends on the specific deal. We have just launched a free Audience Analytics product that publishers can use to develop the content on their site and sell their ad spots as premium inventory - this is a free service.
Our goal is to make this a perfect partner to Google Analytics, where GA gives you excellent data about the stats of your users, Audience Analytics tells you who they are, and what motivates them.
We'll soon be providing tracking code and an inference service as well. We are also in discussion with a number of Ad Networks for to white-label this product. Currently we are working primarily with publishers to help them collect and use the data themselves to personalise content and deliver more relevant advertising. We are in the process of opening up our data for buyers to target against and we'll be publishing more detail on this in the coming weeks.
Can you discuss your research methodology? How do you know what an image means for a user? We're replicating the instantaneous decisions that we all make on a daily basis and, by looking at the pattern of these choices, we understand the core traits of an individual.
It is the pattern that is all-important, as well as the individual image choice. One way to think about it is to consider a consumer standing in a grocery store in front of a wide range of products.
Not everyone buys the same brand and we make choices for a whole variety of reasons, such as color, font, packing material, lighting, price, brand values etc. If you then look at the assortment of products in someone's basket at the grocery counter, you will often see a pattern to their choices. Our job is to make sure that with each question, we are placing a variety of realistic choices in front of the user. We score each image using a patented methodology and learn the patterns of choices based on the scores and tags that come from our taxonomy.
I can't go into the methodology in detail as it is proprietary. Responding to images elicits an instant emotional response that is inextricably linked to our core personality traits.
We work with many different disciplines of psychology and have drawn in particular on the 'Big 5' Personality Profiling methodologies to develop our quizzes and guide the image selection process. Depending on campaign types, marketers can target audiences by demographics, lifestyle, brand preference, personality and shopping personality.
Personality and shopping personality audience data is the core component of the VisualDNA launch. While some consumers are constantly looking for new ideas and the opportunities to trial new brands, others tend to be more resistant to change.
Personality-based audience data simply enables brands to more precisely target consumers based on individual motivations and habits which are core diverse human traits.
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