Is AI used in Salesforce
Artificial Intelligence in Marketing
Whether natural language processing, recommendations or data-based decision-making when segmenting target groups. AI in marketing is more present today than ever.
AI in marketing, no problem thanks to Marketing Technology
Even if the technical possibilities have long been given, marketing with the help of AI means rethinking. Customers are no longer surprised by personalized and suitable offers; they expect to be addressed with relevant information. 52% of users even now say that non-personalized communication is a reason to change brands. A 360 ° view of the customer is therefore essential.
Meet growing marketing expectations
Given the infinite data sources and interfaces, it is often easier said than done to provide your customers with the right information at the right time. It is not without reason that the use of AI in marketing is increasing year after year, because the pace can no longer be maintained with conventional methods. Ultimately, you can no longer manually select the right offers in a newsletter. The idea of a general newsletter is also being replaced more and more. The initial setup and the selection of the appropriate modules and signals for the automation should, however, be carefully considered.
Use cases for AI in marketing
Let's take a look at the fields of application of AI in daily marketing operations. AI can help get to know customers or potential leads better. Based on user behavior, certain clusters, similar user groups or relationships can be recognized that would otherwise not have been recognized. For example, customer groups from a certain product segment with upselling potential for a related product.
Of course, the subject of personalization is an obvious one. Here, however, not only the content, which is composed of content blocks, personalization variables or products from a catalog, but also the shipping volume and the time can be selected individually based on customer behavior. At least now you have reached your limits with manual measures.
Smarter decisions can be made through the use of scoring models and bots. In the first step, questions are answered by a bot and only supported by a service agent when the bot is unsure. By using scoring rules, only those contacts with high potential for a deal are passed on to the sales team.
Smart analyzes are further supported by the use of AI. In this way, the algorithms recognize relationships in the data and point them out. The data analyst can then decide what to do with this information. Using multivariate tests, different combinations of a mail or landing page can also be mixed together to create the best variant and adopted if the results are significant.
Salesforce Einstein for Marketing
Salesforce Einstein is the AI layer of Salesforce, which is located across all Salesforce clouds, including Marketing Cloud and Pardot. Einstein relies on the following components:
- Discover: Insights that create clarity about the customer
- Predict: Predictions and forecasts
- Recommend: Proposal of the next best action for the customer
- Automate: Automate routine activities
Einstein supports marketing experts in saving time, making better decisions and reducing routine activities to a minimum.
Sentiment analysis and image recognition
Social Studio supports the analysis of behavior on social media, not only evaluating sentiments to postings, but also evaluating billions of images via Google Vision. Image recognition can be trained so that it recognizes the placement of logos, products, etc. and can point this out to a social media manager accordingly.
Cross Device CDIM & Lookalikes
Tracking customers across devices is a major challenge for many marketers. Einstein Cross Device Tracking helps and with Audience Studio also allows the creation of lookalikes, i.e. groups of people who are very similar to a reference group. Einstein also supports the smart segmentation of target groups.
Einstein recognizes the content of the images that are used in mailings etc. and automatically adds tags to them. Journey analytics then shows which combination of journey steps achieves the most success. Einstein splits can be used to calculate the probability based on user behavior as to which journey path is more likely to lead to success or which path would be better suited for which persona group.
Classic recommenders are known and can be used in emails with Einstein recommendations. Areas of the website can be tagged and, based on this, the appropriate content can be displayed in an email.
If you want to analyze your campaigns in more depth, you can't avoid Datorama, Datorama allows you to identify the top and low performers in marketing campaigns and act on them.
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