Today, solutions based on Artificial Intelligence have an increasingly role because of the increasing need of using first-party data. The collection and analysis of first-party data is assuming indeed strategic importance in light of recent cookie-less initiatives. Unlocking the enormous potential of “good data”, that is, those owned by companies because they are collected directly on their channels (websites, apps, CRM, chatbot, ERP, …), is and will be one of the hottest topics for the next two years in marketing, especially in web marketing world.
Last January, as part of the Privacy Sandbox initiative and motivated by the respect for users, Google has declared that it wants to follow a cookie-less policy and therefore Chrome within two years will no longer support third-party cookies. Apple’s Safari has done the same; Mozilla’s Firefox and Microsoft’s Edge have already allowed customers to block third-party cookies.
Companies that have bought and used third-party cookies so far, whether operating in the Retail, Publishing, Consumer Goods or other sectors, must now quickly think about collecting, integrating, analyzing (necessarily algorithmically) and activating first-party data. Even more important, there is no time. They have to do it right away because machine learning algorithms need time to be trained and give results.
No to third-party cookies
ln March 2019, Sean Downey, VP and Media Platforms of Google, had written that in the previous four weeks over 160 million users had reviewed their Google accounts to change privacy settings. In particular, they had reviewed the data that Google could collect and the types of ads to be exposed to (Google 2019 data).
Google’s cookie-less policy is part of this strategy and, consequently, tracking between one site and another will be blocked. For some Marketing professionals, it could be a “cookie-apocalypse”, for others a new challenge, a revolution that will offer new growth opportunities
First-party data prospectives
First-party data are proprietary data, collected and extractable by the company through its own channels, digital or not. They are much more respectful of customer privacy, since they are based on a relationship of mutual trust, and they have strong potential in terms of marketing personalization. However, this type of data can express their maximum potential only if properly analyzed and integrated. In fact, customers travel different paths online and offline: they look for information and products using their home or office computer, their mobile phone or by talking to smart speakers or by calling customer services or by going to points of sale or interacting with a chatbot, and so on. All traces and interactions must be meticulously collected, respecting privacy as well. This is the only way to have a unified view of the customer.
In order to do what has just been described, you have to overcome the internal silos and set up a centralized data lake, a large archive that collects data deriving from all company proprietary sources previously mapped, i.e. data collected from all possible channels and touchpoints. To extract value from data and transform them into insights and actions, human intelligence must necessarily be supported by artificial intelligence technologies capable of managing a similar amount of data and all the correlation variables between them.
First-party data: BCG research
BCG (Boston Consulting Group) has analyzed in a recent research the ways in which marketing professionals currently use first-party data to consolidate trust and relationships with customers. The results? Whoever connects all the proprietary data sources achieves better results (even doubled) and optimizes the budget, significantly improving the cost-benefit ratio.
Although 9 out of 10 professionals declare the importance of proprietary data, research has shown that today only 33% are actually able to collect and integrate data from multiple channels and that only 1% use these integrated data to provide customers with an omnichannel experience. Therefore, there is still a lot to do and it is urgent!
HOW TO USE FIRST-PARTY DATA
First-party data: two-way exchange
Customer first. In 2019 Salesforce.com conducted a research that, once again, highlighted consumers’ concern about the collection and use of their data in spite of new European regulations. However, the concerns should not be interpreted as refusal of data processing; indeed, the BCG research cited above has found out that users are, on the contrary, very likely to provide their data when they trust the company.
According to BCG, best practices arise from a fair and transparent two-way exchange of values:
- the company offers a better customer experience and a marketing more tied to customer needs
- the customer provide the company with information trustfully, in exchange for assistance and personalized offers.
For companies, the fundamental point is therefore to do marketing responsibly, adhering to privacy regulations and customer needs.
To do so, a good data management is mandatory and implies a double action by companies:
- an internal action, aimed at establishing the way in which to collect, manage and use data.
- an external action, aimed at defining the methods of interaction with customers for data collection, ensuring that it is always aimed at creating positive experiences.
Use of First-Party Data: the three stages of the process
Based on the research conducted on first-party data, in order to make the flow of value between companies and customers work, BCG has hypothesized a process divided into 3 parts.
- establish a data strategy that supports business goals.
- collect, store, and combine consumer data from multiple sources.
- analyze the data to put them at the service of marketing activities, in all phases of the customer journey.
How to build the strategy
Having a data strategy to support business goals means knowing what data to collect and how to achieve them. It is essential! In case of already acquired customers, the goal could be to create tailor-made experiences that favor loyalty, cross and up selling and therefore increase customer lifetime value. For new customers, the goal could be to identify and suggest the product that meets their needs, even if not explicitly stated. Overlapping the information between channel performance (e.g. of the site) and customer interaction, it will be possible to create an experience increasingly relevant over time.
How to collect data
Many companies collect first-party information from web browsing, from interactions with online ads or through a point of sale (off-line). The professional and mature marketers must now connect the collected data by integrating it. By connecting customer service with a chatbot, for example, or by using loyalty cards to connect in-store purchases with online purchases.
However, it is always necessary to develop new data collection methods, creating new and truly useful interactions with customers.
Analysis and activation
The simple collection of data obviously does not lead to anything. BCG research has shown that only when data sources are integrated and linked to the activation of marketing, companies record an increase in ROI.
Companies can use first-party data in different ways, ranging from basic data (e.g. audience definition and lead generation activities) to more advanced data (e.g. predicting consumer behavior and future trends). A particularly interesting use is related to the recognition and activation of most important customers, identified through specific scoring methods as more likely to purchase. This activity that also allows you to minimize or cancel marketing costs on customers with low or no interest.
How to collect data and at the same time consolidate the relationship of trust with customers? In BCG report, 3 enabling technological factors are highlighted:
- centralized data lake
- data integration
- artificial intelligence algorithms.
First-Party Data and 3rdPlace’s DataLysm solution
The challenge for marketing professionals will therefore be to unlock the potential of first-party data by analyzing, integrating and activating a huge amount of detailed information that perhaps not everyone knows to have.
DataLysm is the Augmented Analytics customer data platform, developed by 3rdPlace to allow companies to be more effective in their marketing actions via high personalization. It is made possible by the analysis and integration through Artificial Intelligence of first-party data, in particular those related to online actions and offline customers.
DataLysm collects first-party data in a data lake, algorithmically integrates and analyzes them, unlocking all their potential through subsequent marketing automation actions.
The platform learns indeed distinctive elements of each individual visitor from all company proprietary channels, it transforms them into value-added clusters based on calculation of purchase prosensity, lifetime value and churn probability, and it identifies and activates for each of them specific actions to generate business.
Collect quality data in respect of customer privacy and sensitivity and, following the analysis, activate specific relevant and effective marketing actions on customers: this is the goal of companies that choose DataLysm to exploit the full potential of first- party data.
This goal is valid not only for large companies, but also for SMEs that want to grow and recognize the value of doing it in a data-driven way, to adapt more easily and flexibly to increasingly evolving situations. The affordable costs of DataLysm allow it.