The tip of the iceberg: marketing

How can the Data Lake revolutionize a company’s marketing strategies? What are the advantages of data enrichment processes? And then why can Artificial Intelligence and Machine Learning be considered marketing (and sales) allies? Finally, what are the five technologies that will have the greatest impact on the future of marketing? We have tried to answer all these questions in order to offer an overview and to emphasize how the different areas of an organization work (better) in tandem and not in an isolated and independent way. Let’s start!

Data Lake, a revolution for the marketing strategy

A Data Lake enables tremendous improvements in agility, transparency and responsiveness to the business, particularly for the type of data marketers work with. By now we all know that a Data Lake is a data repository that allows you to store and process all data from different sources in their native format, without the need to pre-structure them. You can collect and enter data from any marketing source: images, CRM, marketing automation, web analytics, e-commerce, transactions, point-of-sale, social media and third-party data. Therefore, once all the data has been extracted, enriched and analyzed, it will be possible to build a 360-degree view of the prospect journey and the customer journey: then it will be possible to identify all the end-to-end marketing activities that actually contribute to the turnover.Starting from this analysis, the marketer will be able to structure their strategies based on those that are most successful for their business by monitoring them, evaluating them and possibly improving them in real time.

Where does our user come from?

One of the advantages for marketing when using the Data Lake is undoubtedly that of being able to uniquely track and identify the user from the data acquired in different touch points, in order to accurately attribute the origin of the conversion from Prospect to Customer. Not only that, you will also have a unified view of the entire customer experience, thanks to the integrated view of all platforms, all silos and all channels. In this way, thanks to a better knowledge of its customers, marketing will be able to adopt ad hoc strategies and personalize the shopping experience based on the preferences identified along the customer journey.

Data Enrichment: why is it useful?

Data Enrichment refers to the processes implemented to validate, integrate and improve the raw data and information in corporate Data Lakes. Typically, this process has to do with the profiling of users and customers of your company, valuable information that can then be used to develop data-driven marketing strategies, which in turn can lead to a significant economic return. With a complete and updated view of the data, it will be possible to reduce the costs associated with incorrect and ineffective collection / management of customer data, maximize the effectiveness of marketing campaigns, and increase profits from sales and conversions. And again, improving the services offered, using user behavior as a yardstick, it will be possible to exploit the enriched data in order to formulate strategic forecasts on the customer base, useful for anticipating needs and desires, but also for making decisions and processing strategies with the least possible margin of error.

Artificial Intelligence and Machine Learning: the number one allies

According to the McKinsey Global Institute, Artificial Intelligence and Machine Learning could generate value between 1.4 and 2.6 trillion dollars over the next three years by solving problems related to marketing and sales. This data may be enough to understand the importance of AI and Machine Learning applied to marketing, but we will tell you more: according to the most recent State of Marketing Study by Salesforce Research, between 2018 and 2020 the use of AI by marketers it went from 29% to 84%. Artificial Intelligence and Machine Learning are a strategic lever for marketing because they can use algorithms that allow you to make recommendations, create clusters of users, carry out predictive analysis and elaborate advanced segmentation, contributing to the acceleration of revenue growth and the improvement of performance.

The future of marketing