Optimise data gathering for successful digital marketing

According to a study of internet purchasing behaviour conducted by FEVAD and Médiamétrie/NetRatings (the agile) “69% of in-store shoppers searched the Internet before buying in-store” and “52% of on-line shoppers searched in-store before buying on-line.” So gathering digital data is a major task!

Commerce and the digital world are increasingly inseparable. Businesses must now coordinate omni-channel campaigns to offer a connected experience in real time, with an agile approach to content. And to carry out these campaigns successfully, marketing professionals must analyse and measure the effectiveness of their operations in order to optimise them. All this calls for data analytics. But you also need to know how to gather digital data correctly!

Data gathering represents 50% of the work in digital analytics. As spokesperson for the Digital Analytics Hub’Sales agency, I’d like to suggest four good practices that we have found among our customers and in the market for organising the gathering of digital data.

Good practice no 1: think globally

Knowing how to gather data correctly is the key. To start with, the process must be exhaustive. It concerns the whole digital ecosystem: web sites, applications, social networks, media campaigns, registration forms, and even digital devices at points of sale…

Then you need to think outside the box. Data gathering is not only useful for making dashboards in Google Analytics. One of our customers in the automotive industry has taken a detailed long-term approach. Every visitor is identified with a unique ID. This ID is used in all the company’s systems: digital analytics, media, CRM, sales, etc. In this way, the company can determine the return on all its marketing investments with reference to the spending of a customer and that customer’s behaviour (clicking on an advertisement, sharing on social networks, registering for a newsletter).

Good practice no 2: standardise your data gathering

Staying with our automotive company, the second part of its digital plan consisted of standardising the data. A centralised team issues guidelines with a standardised labelling plan. It ensures that these guidelines are applied throughout the group (2 000 sites, 88 countries) by providing training, coaching and recipes for implementation.

This “centralisation” is a widespread phenomenon. We have observed it in several companies with complex organisations and policies of independence from the “parent”. Currently, centralisation guarantees the consistency of data at every organisational level, providing a clearer overall picture to managers.

Good practice no 3: Describing the data gathered

It’s a mathematical truism: if your reasoning and sound and your values are false, the end result will be false.

In digital analytics, we therefore pay particular attention to the quality of the data. It’s quite straightforward, you just have to get your hands dirty and check that the tags are correctly placed on your site’s pages.

It gets complicated when content is updated too much, too often. The risk of errors or broken tags increases considerably. E-commerce sites, comparison sites, travel reservation sites and news sites all encounter these problems every day. And the list is by no means exhaustive!

To resolve these problems, some of our customers use Hub’Scan. This platform scans every page, automatically and exhaustively, and issues a report of errors for correction. The platform can even make corrections automatically with some tag managers. In the last resort, the time saved and the robustness of an automated system are major advantages for digital managers.

Good practice no 4: make sure your business is compliant

The GDPR (General Data Protection Regulation) is impacting the use of personal information. Put simply, digital analytics focuses on anonymous visitors, identified by their behaviour (analysis of funnel conversions, areas of interest, etc.). Therefore, GDPR only has a limited impact on digital analytics, strictly conceived. On the other hand, once a visitor is identified, everything become more complicated for the company. The previously anonymous data are now regarded as personal.

Among the practices identified, the most basic consist of telling visitors about data gathering when they arrive on the site, and amending the general conditions when setting up an account to make it clear that personal data are collected and that the visitor must give their express consent.

This is the approach taken by our watch and jewellery client. When a customer has an appointment in the shop, a six-month digital history is sent to the adviser who will take care of them.

For the internal purposes of the company, to protect against any risk, our vehicle manufacturer has decided only to use anonymous data for activation: the visitor is personified by never named. This player therefore renounces any direct connection between digital analytics and CRM. However, it cheerfully uses customer digital histories to feed its data management platform, itself linked to a content recommendation engine in real time on its site.

Finally, we can mention the case of a telephony operator that has decided to encrypt all the data it stores. This makes it proof against security breaches and database piracy. The work is ultimately carried out on the basis of fictitious identifiers.

Data gathering represents 50% of the work in Digital Analytics.

Marketing teams are the first users of digital data in a company: for optimising conversion funnels, UX and marketing investments, segmentation and the retargeting, personalisation in real time, and so on. They need reliable quality data.

Depending on the size of a company, however, marketing teams are not always in control of their data. This article aimed to explain the importance of establishing sound data gathering bases, or at least, to ensure this internally.

If this subject has hit a nerve with you, and you would like a diagnosis of your digital data, don’t hesitate to contact the Hub’Sales teams.