In the age of ‘big data’, and given the huge amount of data to which businesses now have access, it is becoming crucial for them to put in place a relevant data strategy. This is especially true in a world where data is becoming an increasingly valuable currency.
The transition to GA4 (Google Analytics 4) was already shaping up to be a colossal challenge for marketing teams. But the latest earthquake to rock the data landscape is the imminent end of third-party cookies announced by Google for July 2024.
This transition, which has already been made by Apple and Firefox, is forcing companies to rethink their customer data collection strategy and therefore their marketing campaigns. In this article, we share some practical advice and effective levers for updating your data strategy.
Why do you need a data strategy?
In a world where lead acquisition costs and the cost per click of the main advertising networks are exploding, companies are being forced to rationalise their marketing efforts. They can no longer simply sail by sight and adjust their campaigns according to their performance, a posteriori.
To invest their marketing budgets in the right channels, on the right messages and with the right audiences, they need to base each of their decisions on hard facts. And these proven facts take the form of customer data.
These include a wide variety of information, but also of formats. Il peut s’agir de données démographiques ou comportementales, de fiches contact dans une base de données CRM, d’historique de ventes ou d’échanges avec le chatbot du service client, sans oublier les commentaires sur les réseaux sociaux.
Collecting data, in sufficient quantity and of good quality, is essential for :
- Make business decisions based on tangible, verifiable evidence;
- Anticipating consumer trends and meeting consumer expectations;
- Offer more suitable products or services;
- Personalise your message and offer a better customer experience than your competitors.
The challenge of personalisation in marketing
This last point is very important to remember. It is, 74% of consumers say they are frustrated by receiving marketing messages (in the form of sponsored advertising on social networks or email campaigns) that are not tailored to their needs.
Companies that don’t adopt a personalised marketing strategy are therefore more likely to be throwing their money away (by sending the wrong message to the wrong person). But they also risk devalue their brand image by giving consumers the feeling of being spammed and increasing their advertising burn-out.
But the key to personalised marketing is to have the right tools for collecting, analysing and activating customer data.
The 4 key elements of a data collection strategy
Any good data strategy needs to answer the following question: how do you collect data, ensure it is relevant and use it effectively?
Companies must therefore adopt a multi-dimensional approach that includes :
Relevant data collection tools
69% of consumers are more willing to interact with a brand that offers games or interactive marketing campaigns with prizes to be won. Companies therefore need to diversify their data sources by making the most of gamified experiences.
These are all the more relevant in a cookieless context. En effet, le marketing interactif offre des sources de données plus fiables et RGPD friendly. Les informations collectées seront considérées comme de first-party data, i.e. data shared directly by users with their explicit consent.
A data analysis tool
Collecting data is not enough. A good data strategy also relies on the systematic and meticulous analysis of this information.
The tool chosen by the company should preferably offer a visual representation. Data visualisation will enable all teams, even those least at ease with data, to draw relevant conclusions in terms of marketing strategy.
Identifying the right frequency to collect data
Brands need to be able to rely on relevant, regularly updated data. However, it is also crucial not to put too much pressure on users. Today’s users are more concerned about protecting their personal data.
To strike the right balance, brands can not only rely on relevant incentives to share data (such as the prizes in a marketing competition, for example). But they will also need to establish a marketing calendar to ensure that their various campaigns are sufficiently spaced out.
A data activation strategy
As already mentioned, a good data strategy should above all help the company to make better decisions. It will be used primarily to optimise its marketing efforts, in particular by delivering a personalised message to each customer and prospect.
A solution like Adictiz makes the most of the data collected. For example, companies can use it to segment their target audience, then send automated emails and personalised offers.
How to develop your data strategy
Now let’s get practical. Here are the 3 essential steps to develop a solid data strategy.
1. Define your objectives
Data collection can enable brands to optimise every stage of the conversion funnel. However, it is crucial to identify those that are the most strategic for the company, so that efforts can be focused in the right place.
A brand that has just launched, for example, could focus on lead generation. A company with a low repeat purchase rate, on the other hand, should concentrate its efforts on providing personalised offers to build customer loyalty.
2. Create targeted collection campaigns
Depending on the objectives set and the audience, the company can then run targeted campaigns. The key is to diversify sources, using a mix of :
- digital: via competitions on social networks, as well as post-purchase satisfaction surveys by email;
- and retail: via interactive terminals or in-store events, for example.
3. Test, analyse and optimise
A good data strategy serves all stages of the customer journey, from identifying new leads to conversion levers, not forgetting post-purchase loyalty. To measure the quality of your data and the relevance of the marketing decisions you make on the basis of it, AB testing is crucial.
Defining relevant KPIs will make it easier to analyse the performance of each collection scenario. These metrics must, of course, be aligned with the objectives chosen for the data marketing campaign.
The company can then put in place a virtuous loop consisting of :
- testing new strategies,
- analyse their results,
- and continuously improve its data collection process.
Adictiz supports you at every stage of your data strategy. From creating and distributing collection scenarios to analysing and activating your customer data, find out more about our all-in-one Playable marketing solution.
