Cookieless Marketing

Wattle Labs has created a "Large Behaviour Model" (LBM) of the human population. The LBM, an analogue of LLM's, which seeks to understand human behaviour, rather than language.

Our cookieless marketing technology uses behavioural psychology to predict behaviour - Without sharing or exposing PII data.

#Cookieless #CookielessMarketing #DigiatlMarketing #CustomerProfiling #BehaviouralModelling #ContextualAdvertising #PsychologicalTargeting #DataScience #BehaviouralScience #Psychometrics #Nudging #Boosts

https://www.youtube.com/watch?v=A1k07nnO4lI

Transcript

Hello CMOs, agencies, and marketers. Currently the world is experiencing the cookie Armageddon. This causes several issues in digital marketing: it fragments your customer view, reduces your attribution accuracy, causes higher cost and less efficient advertising, and creates an over-reliance on big tech. The solutions being offered are better commercialisation of first party data and, secondly, commercialisation of third party data. But all of those solutions involve implementing expensive MarTech platforms, utilising expensive consultants, integrating identity platforms, building customer master data records, data warehouses, and reporting and analytics — and you have to implement all of those things before you even execute a single campaign.

Wattle Labs has developed a large behaviour model of the Australian population. We model every single person living at every single address. We can predict with 92% accuracy everyone's wants, needs, dreams, and desires. And this can be used to commercialise first party and third party data without standing up expensive IT systems and without exposing any PII or sales data between companies. So I'll just get into it and show you how it works.

All retailers need to commercialise their data without reliance on third party cookies. A retailer most likely has customer data and sales data, and quite possibly content and campaign data as well. Customer data typically looks like an ID, a name, age, sex, and location. Sales data typically looks like a transaction ID, a product ID, a customer ID, a price, and a timestamp. This is essentially the MVP of a retailer's first party data. Content and campaign data works in exactly the same way, and our systems can handle all of it.

The agency's job is to take this data and execute campaigns. So let's start with first party data — that is, an agency advertising back to your own customers, without exposing PII data and without endless IT cost. What we can do within the client's systems is take all the customer data and profile it to create personas. These personas capture the psychological, behavioural, socio-economic, and demographic drivers of each and every customer. Critically, they contain no PII data. So we take the customer list and create a whole set of personas.

We can then take the sales data and do exactly the same thing — profile all the transactions to create product personas. Now we have both product personas and customer personas. The task of the agency then becomes really straightforward, because our matching engine — essentially a recommendation engine — can identify the critical factors causing people to purchase a product. That data alone is very valuable and can be commercialised by selling it back to the brands.

We can match which product is being purchased by which persona. So a group of people — customers 1, 2, and 3 — purchased a product, and we can derive the persona behind that behaviour. But then we can also find that customers 4, 5, and 6 exist. They have the same socio-economic background, the same behaviour and psychology, that should really align them to this product — but you're not currently advertising to them. So for first party data, we can help you better understand your customers, commercialise that understanding back to the brands to explain why people are purchasing their products, and then match products back to people at a psychological and behavioural level — uncovering a whole range of people who aren't currently purchasing but genuinely would.

Third party data is just as straightforward for us. We take the client — who has their own customers and sales data — and then all the third party partners, who also have their own customers and sales data. Because we're matching based on behavioural and psychological drivers, we can match across any organisation without ever exposing PII data.

For all the partners, we create personas for their customers and their products in exactly the same way as before. So as the agency, it becomes trivial to match which product from any given partner a customer might want. And it doesn't matter how many partners you have — 50 partners makes no difference. You simply ask: what products from partner one would customer one, two, three, or four like? Our matching engine can answer that without sharing any PII data. We can also identify that customers over here would like a product from a different partner. So each partner's first party data can be commercialised in a third party context without ever sharing PII.

For each individual retailer, we can maximise the value of their first party data. Your first party data becomes their third party data, and we can create matches and recommendations between two organisations without sharing PII. This is a 100% cookieless matching engine. No cookies, no PII, no binary matching of people. We get to the fundamentals of who a person is and what they want, who is buying these products and what the critical behaviours driving that purchase are, and then we match the psychological and behavioural profiles accordingly.

That's it — that's all I wanted to say. Please contact us if you're struggling with the cookie Armageddon. Have a great day, thank you very much. Goodbye.