How to use data to optimise targeted advertising campaigns

This article originally appeared on The Drum on 13 September.

The growth of big data has seen a rapid increase in the use of data segments to power targeted advertising, the science of reaching anonymised niche groups of people defined by common characteristics.

VisualDNA uses the first-party, self-declared data we generate from visual personality quizzes to create high-quality Demographic, Brand Preference, Purchase Intent and, now, Emotive segments that power targeted advertising.

With multiple factors affecting the performance of a campaign much like effective media buying effective data buying is something of an art form. Programmatic? Not really: data optimisation is done manually, and by smart people. Our top tips for using data segments successfully:

1. Beware of ad-blindness! Don’t over-impress…

A car brand running a campaign of 50 million impressions will likely want to reach people in-market for a car. In theory, a segment such as “Car Buyers” would yield great results, but if that segment comprises just 500,000 people then each user would see 100 impressions a month. Not good.

Over-targeting an audience that’s too small bombards your audience – reducing conversions and increasing CPAs per impression. So define the total number of impressions served and work back. If an average of 15 monthly impressions per user is about optimal on a cost-per-impression/ conversion basis, then a 500,000-strong segment is only enough for a reach of 7.5m impressions.

A run-of-network to make up the remaining 42.5m impressions means you’re reaching a wider audience, reducing the average data and media cost per impression –plus you can test the performance of the data. Data can dramatically increase conversions, but you won’t hit that uplift and justify your data spend if you over-impress.

Trading desks know this of course but thinking about data at the media planning stage helps them buy better segments. The IAB’s Data Usage and Control Primer is a great intro for anyone using data as part of a campaign.

2. Use analytics tools to define and build your audience

At face value, choosing segments should be straightforward.  Quality data, demographics from trusted providers such as Experian, and intent data from sector specialists should perform. Descriptive VisualDNA segments such as “iOS Preferrer”, or Emotive segments, built from self-declared data collected through our quizzes, are also obvious ways to build an audience.

But not all segments are self-evident. Audi, for example, might intuitively buy an “Audi Preferrer” segment from one provider, but it might be that a “Luxury Holiday Preferrer” segment from another provider is a better fit for their brand.  Adding such a segment to a campaign would increase the size of the targeted audience, improving the performance of a campaign

In addition to industry-standard audience insight tools such as Quantcast, WHYanalytics profiles a website’s audience to show which VisualDNA segments rank most highly – powerful new insight for publishers, ecommerce, advertisers, media agencies and brands.

Such tools help publishers meet high-value brand campaign briefs or identify niche audiences while, in ecommerce, online stores can personalise around personality. Plus agencies can pick the best segments to build a targeted brand advertising campaign.

3. Set the right metrics, test the data & monitor throughout.

What does success look like? A Victoria’s Secret creative showing an attractive woman sat on a beach may attract a disproportionally high number of clicks from men, suggesting that male-skewed segments should be used, at the expense of other female-oriented segments…

So it’s about conversions above clicks but track both with a short, un-targeted, “Discovery Phase” at the start of the campaign against each creative.  Whether it’s a direct response or brand campaign, by analysing the ad (impression beacon) and conversion page (conversion pixel) we can tell you which segments are responding. From here you can optimise around the right segments, and have a benchmark from which to measure performance.

We’ve created WHYanalytics to help publishers, ecommerce websites, advertisers, brands and agencies better understand VisualDNA data, and use it to create a better-personalised experience for their audience – we’re working with our beta partners to build more features and functionality that will make it easy to track. Free to use and easy to deploy, try it out at why.visualdna.com/analytics

Infographic – how VisualDNA creates emotive data from quizzes

visualDNA-infographic-howinferenceworks

Display Advertising- – What’s Next? VisualDNA at Figaro Digital

Yesterday I was fortunate enough to speak at Figaro Digital’s Display Advertising Seminar at London’s Hospital Club, on how innovation in advertising is changing the market.

It’s an area that’s undergone dramatic change in the last 5 years as the web has matured and in particular over the last 3 years with the rise of real-time bidding, primarily in the UK and US. We expect this change to accelerate in the next 12 months.

A big part of what VisualDNA does is provide data that allows advertisers to reach very specific audiences. The data market is growing fast and has many providers: mass and niche. But what makes us different is the lengths we go to understand people: rather than guess what a person might buy by crunching reams of second-hand big data, we build a rich picture of who they are, and why they do what they do, by asking them first-hand through an online personality quiz.

We are able to successfully scale these rich profiles across our vast publisher network, 150m cookied users globally – which puts us in the unique position of being able to help advertisers reach large number of consumers on an emotive level, not just demographics or inferred purchase intent.

During my talk I touched on three big things driving change in display advertising:

1. RTB platforms are innovating upmarket
Having started out with a focus on buying remnant inventory cheaply and at scale, the media buying platforms are innovating themselves upmarket. It’s possible now to seamlessly manage entire campaigns through these platforms and put data-driven advertising at the heart of a campaign. They are grabbing a bigger share of the display-ad pie, and making the process more sophisticated: great for data providers such as ourselves.

2. Brands are looking beyond demographics
Media companies recognise that consumers can no longer be conveniently bundled into old-school demographic groups – which is why creative agencies develop sophisticated segmenations based on who people are (emotionally) and why they behave in the way they do at any given time. But yet most media buying is about guessing which demographics and vertical segments match emotional profiles. This is changing – VisualDNA is already innovating here with emotive segmentations but we can expect newer solutions as the market moves to meet brands’ desire to move beyond demographics.

3. Data is the media buyers’ secret weapon
When all that matters to trading desks is performance vs CPMs, it’s tempting to dismiss data and buy on price alone. Used well, data is worth the money and delivers results for clients – but can be confusing or daunting if you don’t know how to use it.

But if targeting the 10% most likely to convert makes that segment 10 times more valuable, it’s easily worth paying twice the price and buyers are getting better at optimising their campaigns. With more buyers working out how to use data, demand will filter up the chain – motivating agencies to be even more innovative in their creative. Data is the media buyer’s secret weapon — but only if you take the time and resource into testing.

Want to see more? You can view our Prezi here.

Reaching beyond demographics

I joined VisualDNA earlier this year from Google to lead the media sales team – and after almost 10 years in the business the technological advances have been mind-blowing. Exciting as this is, the art of marketing, media-buying, timing and nuance is being replaced by machines. Define your audience, set your budget, input your criteria into your media exchange of choice and off you go. It’s a growing trend too, some 25% of all UK online ad spend in 2012 ran through RTB platforms and most experts expect that percentage to grow further and faster.

But as the ad world becomes more efficient and effective at trying to reach the right person with the right ad at the right time, it’s getting a bit soulless, disconnected from real human connection. For all the insights the internet can deliver, and disruption it’s caused to traditional mass media companies – advertisers still rely largely on demographics and mass when buying media online.

Demographics hail from the Mad Men age. It was the National Readership Survey (NRS) that first carved people into ABC1/ C2DE groups – classifications borne out of a regimented 1960s class system where your preferences were inferred from your buying power with the ‘professional or higher managerial’ upper middle-class grade A at the top to Grade Es ‘at the lowest level of subsistence’ – dependent on the State – at the bottom.

Simply put, demographics tell us little about ‘who’ our customers are – and even less about ‘why’ they are motivated to buy stuff. Kantar’s Target Group Index (TGI), Experian’s Mosaic and IPA Touchpoints all provide a more nuanced way for media owners, agencies and brands to segment and reach an audience, since they are enriched by multiple behavioural data sets (clicks, browsing, purchases and so on). which is great. But they still don’t get to the core of what makes people tick. It’s all too assumptive, ‘umbrella-level’ data…and lacks human feeling and ‘real’ insight.

We know smart brands want to understand people on a deeper, more emotional level, and this is the real opportunity for VisualDNA. No other adtech company, to my knowledge, goes anywhere near as far as we do to understand what actually makes people tick.

First, our in house team of psychologists, mathematicians and designers iterate  and refine our quizzes to an astonishing level of detail – this is why the data we collect and the profiles we can build on an individual are both rich, accurate and at mass-scale.

Second, we capture emotive data –  and we’re approaching a point where we can scale it too. Brands define their ideal customers by their emotive characteristics so it makes sense if they can buy media against those characteristics too.

And third, we’ve proven that our audience targeting technology actually performs. We match captured behavioural data from our network with that of our quizzed users, and we can match any custom campaign brief we receive. Our sales are growing at an incredible rate – which proves to me that the demand is out there for quality data. We are seeing a larger appetite from Media Agency data teams, wanting to take in our data, digest it, and supply out to their Advertisers as ‘portfolio management’ data. It’s great to be at the heart of this ‘real’ consumer insight and business intelligence.

Sitting behind this is a broader vision to humanise the web by helping businesses to truly understand why their customers behave in the way they do – and meet their needs in real time.

It’s a really exciting time, and while we’re not saying the end is nigh for demographics and mass media, there’s a real opportunity to do something different and we’re relishing the challenge.