Machine learning has become entrenched in marketing operations. CRM (Customer relationship management) platforms are connected to social networks and many customer data are available thanks to data management platforms.
Grégory Labrousse, founder and CEO of nam.R, a society that deals with open data and artificial intelligence to find new effective solutions, will explain this more thoroughly.
Description of new practices.
The sources of data used in the marketing of customers are diverse and the traces left online by Internet users are numerous.
Marketing specialists can easily observe consumers through their online purchases, applications, conversations on social networks, browsing history or search engine queries.
I. The ability of marketing departments to collect and process customer data revolutionizes two aspects of business: In the first place, a great change of attitude can be observed: instead of intuition, now one depends on consumer trends, consumer knowledge and the analysis of real behaviors. This is one of the greatest strengths of the data: it analyzes the existing data to bring to light new customer behaviors that were previously not suspected.
II. Once put into perspective, these data become information that provides real added value in the segmentation, targeting and management of customer relationships.
For example, a telephone company mapped the profiles of its clients and found out who were more likely to switch to the competing companies and with this information, devised strategies to contact and retain them.
Consumer data and points of contact
“Connecting with consumers in a personalized and ad hoc manner is a key challenge for advertisers” recalls Labrousse. As part of his sales strategy, both online and in retail, he tells us that “brands make use of geolocation-based tools such as geofencing and reorientation to be able to respond immediately and reach their potential customers automatically”. “The knowledge of each of these data is of the utmost importance” he adds.
Geofencing allows advertisers to send promotional messages and advertisements directly to a consumer’s mobile phone when they are near the mall or a store of interest. This method has yet to be perfected by advertisers and retail professionals.
Retargeting allows brands to buy web advertisements in real time to track a visitor who has recently visited your website. Although it is an effective strategy, it sometimes leads to a sense of tracking or intrusion among Internet users. To optimize the use of data and satisfy consumers at the same time, some rules must be followed.
Overcoming obstacles in the use of Big Data
When an advertiser invests in big data to strengthen its marketing strategy, it must deal with some key points:
First establishing a dialogue with customers is important. It is essential to reassure them and educate them about how their data will be used. This approach is useful and effective. Studies show that customers are more likely to share more personal information if they feel they are making a profit. “Customizing a product or co-creating an
offer also encourages the exchange of data” adds Labrousse.
In addition to customer approval, switching to a data-driven model also requires management commitment. Silo organizations are enemies of data-driven approaches.Therefore, it is necessary to prepare for internal negotiation and adaptation before data collection
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