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Precise Marketing | Digital marketing for digital dinosaurs

Remember a couple of years ago a company called Cambridge Analytica?

It was a big scandal for FB and it opened our eyes on certain topics, namely how FB uses our data.

Interestingly, CA was also very successful at what they were doing. A world class digital marketing case study.

What can we learn from it? Stay with me and I will show what marketers, FMCG marketers in specific, could learn from it.

In 2018 a movie-like scandal came up. It touched American elections, a company called CA and FB amongst many other players.

In a nutshell CA obtained a series of datapoint of more that 100m Americans and used those data to support one party.

So far, nothing particularly interesting and I don’t want to get into politics here.

What is really interesting is the marketing lesson that they gave to the world about how to use those data.

Let's recap: CA managed to cluster relevant target groups and use data with laser precision to define what really motivated them to vote. They then used those profiles to develop tailor made relevant messages. Lastly they used the same data to reach them precisely through media buying.

For example, take the topic of gun restriction: 1) they were able to use FB data to profile different clusters of people, say for example cluster one women worried about immigration and cluster two older men who own guns.

By using their data, they were able to serve them different ads with different messages, example

- cluster one women worried about immigration were bombarded with message messages like: they will take away your guns and you won’t be able to defend yourself from immigrants;

- cluster two the older man target them with a different message like: they will take your right to own a gun and destroy the values of this country

Why is this relevant to us?

Because this is marketing excellency. In our world we call this “Precision marketing” and this is what I want to talk about.

What is precision marketing and why is it relevant for us?

Precision marketing as I see it is a marketing practice based on the principle of “relevance”.

Consumers are bombarded with thousands of communication messages everyday in every platform at every pointing time.

Whilst digital has dramatically improved our ability to target the right people with the right messages, still there seems to be a lot of organic waste, meaning: a lot of the messages we put out there are not relevant for people.

This happens to be particularly important for FMCG products as they, by implication, want to target mass market consumers.

With precision marketing we make sure that our communication activities are tailor made on the most relevant cluster of consumers in order to make sure that the messages we put out there are relevant and will generate the behaviour we want to provoke, whether trying a product, switching brands or consumer more of a specific product.

Now, the idea of precision marketing is not new in the digital landscape. In fact most of the advertisements we see in our digital media, whether ads on our facebook wall or those banners that seem to follow us everything we do online, are based on the principle to serve the most relevant ad in the most relevant place at the most relevant time.

What is interesting for me is how can this principle be adopted for FMCG mass market products at such big scale?

Let’s step back in time a bit.

In the past we used demographic to approximate consumer intent and inform our targeting and creative work.

We started from a generic target, say women 25-35 years old, certain socioeconomic classes, living in certain areas, certain income, education levels and so on.

From this set of information we would brief our communication agencies to develop communication activities.

Planners and creatives in communication agencies, would deepen down our analysis, trying to define a relevant insight on which to build relevant communication.

We would end up with one message for a big generic target group, encapsulated in one or more execution broadcasted in one mix of different media.

Result? One size fits all messages.

We assumed that those who are in the same demographic have the same interests and needs, and more importantly were triggered by the same messages.

So we traditionally adopted a ONE SIZE FITS ALL approach for marketing plan.

This was due to several limitations first, the ability of the media channels to narrow target, think about TV for example,

Second, production budgets, it would have been impossible to produce 4 TVCs for 4 different subsegments and lastly a lack of data to inform our planning strategy (how to be sure of what sub targets are relevant within a specific group?)

Now, fast forward a little and back to 2022.

With more than 4h spent in front of screen everyday on average, a part of ruining our concentration and social life, we leave around an immense quantity of data.

Those data is continuously collected, aggregated and used to refine algorithms and targeting activities.

YT, FB, google, IG, Linkedin, all the social media platforms we use on a daily basis are in the business of selling our own data to marketers (ourselves by the way)

Those data can be used to refine our ability to deeply understand what motivates people and as consequence serve them tailor made communication that’s more relevant to them.

Here is where we can see how Cambridge Analitica’s case study it is actually a world class marketing case study if seen from this very specific perspective.

So, let’s dig into this; how do we plan for Precision marketing?

We already introduced the concept of Digital Persona.

Now something makes Digital Persona very different from traditional communication targets, and this is the fact that we can actually follow those persona in their “path to purchase” or as we call it,“digital journeys”

Understanding the digital journey allows us to understand the critical touch-points where we can interact with them as well as calibrate our messages to make them relevant at the right stage.

When someone uses a specific touchpoint related to this mission, they are implicitly signalling an interest.

Through Precision marketing we will plan our communication to intercept this interest and deliver advertising messages accordingly.

But tailor making the message is not the only advantage of this approach. By using specific marketing platforms we could work on a number of different signals and adapt the communication message almost instantly.

Those platforms - example Jivox, Sizmek, Criteo - allow brands to create multiple combination of advertising that are served when a specific trigger happens.

Let’s look at one platform called Jivox for example where we can play with 3 specific group of signals:

  • people

  • interactions

  • moment

People: This means that certain ads will be displayed only to specific targets

Interaction: Or could be served only in specific stages of the funnel (example only to users or only non users of the brand)

Moment: lastly specific ads could be served only in certain specific context, example when the target is in a specific place, or when the weather is in a specific condition, the temperature reaches a specific level or even when a certain sport event happens.

An example?

A popular personal care brand wanted to launch a new line of shower gel.

Their target was women 25-35 yo higher social status

They realised there were at least 3 groups

- beauty enthusiasts - a more generic group that we knew were heavily influenced by KOL

-users of premium brands - a more sophisticated group willing to spend more for unique ingredients

- natural lovers - a specific group triggered by natural products, natural ingredients, no chemicals, no animal testing and organics

We worked hard to define for each group 1) key insight, 2 digital touchpoint 3) triggers and barriers towards our category and brand 4) digital journey

All those data allowed us to clearly define a key trigger for each group and develop a series of ads that we planned for best distribution.

In specific

- beauty enthusiasts where targeted with KOL benefit ads and retargeted with range products

- users of premium brands where targeted with one variant ad containing a specific premium ingredient and then retargeted with range ads explaining how the ingredients were used

- natural lovers where first targeted with a brand message communicating about the natural ingredients and after that retargeted with range messages about zero chemicals

We didn’t use contextual targeting in this specific case but for example we did it in other cases when promoting skincare products that protect from pollution. In that occasion we were able to target specific location when the level of pollution reached a certain critical point.

All above resulted in much higher engagement rates than we seen before. Moreover after interviewing consumers we realised that brand attributes like “understands my needs” scored much higher against previous researches.

Now at this stage it is clear that the whole principle of precision marketing is based on data.

Because of data we can track online behaviours

Because of data we can cluster targets in persona that are relevant for us

Because of data we can understand what trigger each cluster

And again because of data we can target them precisely

Cambridge Analitica could be so successful and precise at what they have done because they could get hold of several data points of millions of Americans

The question for brands who want to play this game is: how to get those data and how to manage it especially considering the tightening of privacy laws around the world?

As of this recording I see two main approach we are taking as agency for our clients

The first and most obvious approach is asking data to consumers. Think about the information we give out when we fill questionnaires, when we apply for promotions, when we download white papers for example.

One company used an attractive promotion to collect data. They did this through bots that guided consumers through a series of questions. Questions were tailor made to create profiles.

This approach is expensive and requires time and effort, but is by far the most effective as the brand owns data, can analyse them and manage them.

A second approach is to collaborate with media agencies who have access to a big amount of data. This approach is effective for clients who use those agencies but as third party we have a lot less visibility on data and we need to rely on other parties to manage for us.

A simpler but less precise approach is to rely on main platform data and their ability to precisely target consumers. With this approach we use the targeting capability of each platform but we need to make big assumptions in the planning phase at the beginning of the process, when we want to cluster our main target in relevant digital persona.

Whichever approach you decide to take, data are crucial to inform our precision marketing strategy and execute it in the right platforms at the right time.


In this section we have discussed about precision marketing, what is it and how we can plan for it.

What are the key take outs?

1. It’s important to show the right digital ads to the right target based on SIGNALS the target gives out. With precision marketing we can tailor make our messages on consumers triggers

2. Knowing their digital journey and touchpoint allows us to know where and when to serve the most appropriate content

Although this might not be new for some of you working in certain industries, like e-commerce, when it comes to FMCG however this approach is still relatively new as FMCG brands tend to look at reach first in order to meet the scale requirement that mass markets have.

In this respect I do believe that compromising some reach for the ability to deliver the right message at the right groups, is proven to increase engagement and drive more conversion in the long run.

Hope you're enjoying these posts, please feel free to get in touch!


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