By Simen Moen, Director of Customer Success at ViewersLogic
Picture this: an RFP has landed on your desk from a household-name brand that would be a massive win for your agency, and it’s all-hands-on-deck to assemble the pitch.
You know the incumbent agency has been working with the brand for some time and has hands-on access to its first party data which gives them an unfair advantage.
So how are you going to bring fresh insights that gets your foot in the door? Patching together insights from various channels and platforms – in today’s fragmented media ecosystem – would be a massive resource drain and extremely imprecise.
What if you could access a holistic view of actual consumer behaviour all in one place? This view can be found in single-source data, passively collected from consenting panellists across the country and modelled to be representative of the entire population. This dataset includes information on TV viewing, online and offline purchases, online browsing, search, video on demand and more for the same individual. At a time when data is everywhere but its quality remains questionable, having a single source of truth gives you an edge.
All the headaches of data matching, duplication, and data reliability disappear when looking at passively collected, GDPR compliant, single-source data.
Because it is much easier to analyse single–source data, agencies can find those “Eureka!” moments that might make a brand reconsider their incumbent partner. Not only can they back up their case directly from the best source — real-life and real-time consumer behaviour — but also provide analysis of competitor customers and campaigns.
How to nail a pitch with single-source data
To demonstrate single-source data in action, let’s return to our opening hypothetical. The brand you’re pitching to is a betting company — armed exclusively with single-source data, how could you populate the pitch response?
- Segment audiences: Single-source data allows for infinitely customisable audience segmentation based on longitudinal behaviours. In this case, the client’s target audience of gamblers could be divided into casino, bingo, sports betting enthusiasts (subdivided by individual sports), and more, including parameters that aren’t directly relevant to the sector.
- Go granular: Further split these segments to identify heavy, medium, and light gamblers, filtering out audiences that provide limited room for growth.
- Dive deep into behaviour: What are their other interests? What are their gambling patterns? What other media do they consume? Single-source data reveals behaviours such as app usage, web browsing, what YouTube videos they watch, and even TV viewing habits across both linear and CTV. With this data, you can optimise your media strategy for the pitch.
- Devise a data-centric acquisition plan: Investigate where competitors’ customers spend their time and isolate those that have never used the brand you’re pitching to, then see which channels provide the best chance to reach them. You can also use such samples as seed audiences for online targeting, improving the results of online campaigns.
- Analyse past campaigns: Single-source data stretches back to whenever the panel in question first launched, allowing planners to research prior campaign successes and failures — including those of the incumbent you’re pitching against. Using this data you can show what you would have done differently and explain why it will work.
This same approach could be applied to any number of potential pitching scenarios. Anyone who works at an agency can certainly imagine a time when such insights would have pushed a pitch over the line. But you don’t have to imagine – single-source data is tried, tested, and proven in understanding consumer behaviour, used not only by brands and advertisers but anyone who has an interest in how media affects our lives.
Today, AI-powered single-source data is a breath of fresh air at a time of data fragmentation and signal loss. As the misapplication of AI and other tools threaten to undermine the shared understanding of reality that we rely on to make decisions, combining transparent AI models with the strongest available data will give agencies the edge they need to turn lukewarm responses into RFPs, and RFPs into wins. By bringing the power of truth to your pitches, you’re in a good position to send the incumbent packing.
