We are witnessing in recent years the rise of artificial intelligence (AI). All sectors are directly or indirectly concerned. On the other hand, one of them is (and will be) more particularly impacted: marketing. I suggest you browse 7 trends to illustrate the impact (current or future) of AI on marketing.
Trend 1: Sales Prediction
Artificial Intelligence (AI) allows today to analyze finely many external variables (eg weather, social networks, research done on the various digital devices of the advertiser, sales volumes …) to predict the volumes of sale of a product.
Interest (s): The advantages are numerous and concern above all the logistics (manufacture, storage, transport …). Some examples :
- Knowing the impact of the weather on barbeque sales could store an ideal number of barbecues in stores.
- Knowing the models of dresses or pants most liked, shared … would design and sell on the market models more in line with the wishes of consumers (trices).
Trend 2: Customer/prospect scoring and targeting
Artificial Intelligence identifies the most “interesting” prospects (those with the probability of transforming the strongest) thanks, among other things, to the “look-alike” method. This makes it possible to identify an audience “resembling” the clientele of the advertiser, that is to say, sharing the same interests, visiting the same sites, the same product categories, etc.
Interest (s): Optimization of acquisition costs.
Trend 3: personalization (zoning and editorial content)
The IA tests a multitude of different zonings for the same page, in order to identify the most optimal configuration. In most cases, the solutions are based on the technique of multivariate AB testing and machine learning.
Interest (s): It depends on the optimized content. In the case of a product sheet, we will be primarily sensitive to the rate of transformation, as part of a newsletter of its open rate and its click rate.
Trend 4: customization (product recommendation engine)
The IA identifies and offers the products (complementary, substitution or simply new products) most relevant to the profile of the visitor. Traditionally, customization was based on CRM data. The addition of Artificial Intelligence allows today to add new variables, such as:
- Indoor & Outdoor Geolocation
- weather
- Social networks
- Navigation history
- …
Interest (s): Two objectives are pursued: increasing sales and improving customer satisfaction.
Trend 5: personalization (dynamic pricing)
Artificial Intelligence customizes in real-time the proposed selling price according to the profile of the visitor. Tracking, even if it is now more difficult because of the RGPD, allows tracing the course of the consumer. And therefore to identify, for example, the number of times it will consult the same product sheet, to learn about general sites dealing with the product and / or the associated product universe … Put together, these variables make it possible to understand the interest of the consumer for such or such product, and eventually change the price.
Interest: Increase in sales volume
Trend 6: Chatbots (or Conversational Agents)
The AI, and especially the NLP (Natural Language Processing) and NLU (Natural Language Understanding) allows creating conversations between the man and the machine. More precisely, the NLU makes it possible to analyze a sentence and to extract the meaning (the intention) and possibly its variables (the entities). To learn more about the subject, I invite you to read our article on chatbots.
Interest (s): The use cases are extremely numerous. All sectors can be concerned, the different services of a company also, B2B, B2C, … and thus the advantages related to its implementation are very different from one situation to another.
Trend 7: listening and analyzing social “noises”
Artificial Intelligence allows, among others, the advertiser:
- to know what is said about him on social networks
- to identify promoters and detractors
Interest (s): The advertiser can quickly respond to critics and “defuse” a crisis. On the contrary, he can also reward his promoters and hope that they will talk more about him around him (social networks, relatives, families …)
How does it work?
These new applications are based on different techniques, in particular, machine learning. In general, machine learning is a technique that allows the machine to test different situations, and to know the performances thanks to the autonomous analysis of one or several KPIs.
We find, among others deep learning that allows, for example, to recognize images, people, facial emotions, objects …
The impact of Artificial Intelligence on marketing is a very broad topic and one that is far from mature. New features will appear in the coming years. The unified customer experience platforms ( Adobe Experience Cloud, Salesforce, Octave, etc.) will also continue to integrate new artificial intelligence features into their solutions, whether by purchase or by internal development.
