Companies that seem to have made the shift to AI...

Surveys, studies and other barometers explaining that artificial intelligence is deployed in companies and more particularly in their marketing departments are rare. Here is a selection of articles gleaned from the web on the subject:

  1. "This trend is confirmed by Forrester, which notes that 46% of marketing and sales departments are leading investments in artificial intelligence, far more than other departments in the company."

Extract from the article "AI in the service of marketing: key figures", published August 01, 2019, on itsocial.com

 

  1. "51% [of marketing professionals] are already using AI"

From the article "[State of marketing] Artificial intelligence, a priority!", published June 21, 2017 on frenchweb.fr.

 

  1. "By 2020, 30% of B2B companies will use AI to augment their sales process."

CMIT infographic picked up by several media outlets in September 2018, including the article " AI: what impact for marketers? " published in September 2018 on https://comarketing-news.fr.

 

 

  1. "Retailers are coming out in favor of artificial intelligence and are currently 67% in favor of using it."

From the article "AI is getting a thumbs up from retailers" , published on November 9, 2019, on ecommercemag.com.

 

... but which are in fact few in number

A quick read would lead us to believe that at least one out of two companies uses artificial intelligence in its marketing strategy. We would therefore be easily surrounded by marketers and emarketeers fed with AI who, thanks to their mastery of artificial intelligence, would manage to achieve the objectives systematically mentioned in this type of strategy:

  • personalize their message and increase their conversion rate
  • reliably predict future customer events
  • increase the customer experience and communicate seamlessly with their customers (especially through chatbots)
  • etc

While this is obviously a reality for some companies that are successfully implementing such solutions, let's take a moment to try to measure the profile of these companies. The reality seems to be more contrasted.

 

Artificial intelligence in marketing remains the prerogative of certain companies

The "State of Marketing" study tells us more about the profile of those surveyed. The survey covers 3,500 Salesforce users, including 350 in France, and the majority of respondents are digital natives (57%). When you consider that 73% of SMBs do not use a CRM, the fact that "51% of marketing professionals are already using AI" seems a bit hasty.

Similarly, according to theecommercemag.fr article, two thirds of retailers would use AI. If we look at the base surveyed, we come down to 112 respondents, which does not seem to be significant. Half of the respondents belong to companies with more than 250 employees.

It therefore seems difficult, according to most of the existing studies, to put a figure on the real use or not of artificial intelligence in companies. The number of biases in all these studies remains very high (number of respondents, respondents' profiles, size of companies, geographical areas, etc.). Nevertheless, some trends seem to emerge without any real figures:

  • Large companies remain the preferred target.
  • The digital sectors are further ahead.
  • The use remains the improvement of customer knowledge for the personalization of messages.

 

Many difficulties related to the quality of the data

While some companies are using or looking to implement AI in their marketing strategy, many still face serious challenges. These difficulties can be crystallized around the 5 major myths related to artificial intelligence described by a Forester analyst. Of these, myth number 2 is particularly significant because it speaks to a much broader reality than the single issue of AI implementation.

Myth #2: AI is sophisticated mathematics and algorithms.

The reality: the important thing in AI is the data.

 

Mick Levy, Head of Innovation at Business & Décisions, discusses these difficulties in an interview published on his company's blog:

 "The key success factor is above all to know your data assets well, to master the quality of the data, and to have the ability to activate this data in the service of Artificial Intelligence.

This trend was confirmed by the latest CMIT barometer, conducted in 2019, where 53.7% of respondents (out of 465, 70% of whom were in companies with more than 100 employees) said that their database was insufficiently qualified and 38.4% that it was obsolete.

 

The need for good data sourcing

The success of a marketing project in 2020 (improvement of customer knowledge, increase in campaign transformation rates, detection of business signals, etc.), whether or not it includes artificial intelligence, depends first and foremost on the qualification of internal databases and the acquisition of specialized third-party data.

The first-party data (internal data), the solution is essentially to process and implement technological solutions to aggregate, analyze

For second-party and third-party data, several options are available to B2B companies. The simplest, for generic company data (for prospect targeting for example), is to retrieve data from open data. This article references for example some of the data available in open access.

Database processing is often cumbersome to manage, but it remains an indispensable tool for analyzing your customer portfolio. Another solution: using a partner specializing in data aggregation can be more cost-effective and above all offer more analytical possibilities (multi-source cross-referencing, historization, sectoral databases, etc.).

It remains to be seen how to transform this data (obtained on the web, purchased or simply recovered from its own internal systems) into a sales and marketing performance lever. This is what we will discuss in our next article, which will present a precise methodology for customer analysis and the detection of prospecting pockets.