Einstein for Marketing summarised
AI is marketers main focus and biggest headache. Most prominent statement coming from the 9th state of Marketing meaning marketers rank AI adoption as both their #1 priority and their #1 challenge. Engaging with customers in real time, creating a cohesive customer journey and improving the use of tools and technologies overall is more than ever marketers’ focus. Marketers are leading the game by embracing rapid advancements in technology to better connect with customers and prospects. This article taps into how marketers are fueling their strategy with AI to succeed in that.
Generative AI has captivated the world with its ability to create brand new content like text, imagery, and video. From scaling creativity to automating processes, AI holds a lot of promise. In 2022, 68% of marketers had a defined AI strategy.* Today, 75% of marketers are already rolling up their sleeves and experimenting with or fully implementing AI. However, only 41% of high-performing marketers are fully satisfied with their AI strategy.* Gen AI may have been relatively new, but marketers have been quick to add it to their arsenal. Gen AI use cases rank among marketers’ favorites alongside more established predictive AI applications. As a result, marketers are leaning on both flavors of AI to automating customer interactions, generate content, drive best offers in real time etc.
Salesforce Einstein has quite some functionalities available to answer on the needs to accelerate the customer lifecycle with AI. The abundance of both predictive as generative AI capabilities should help marketers drive the customer-centric marketing they are looking for. Let’s dive into Salesforce Marketing Cloud Engagement and Data Cloud for Marketing out-of-the box capabilities that can drive a better customer experience. There is plenty of the shelf AI that we can use with clicks not code.
*https://www.salesforce.com/eu/form/marketing/state-of-marketing-9/
Future proof your customer journey out of the box AI features
Starting with Einstein Engagement Scoring to drive personalisation that predicts exactly the likelihood of your subscriber to engage and how often. If you would want to know which engagement personas your subscribers are categorised in or whether it is more or less likely for a subscriber to click on a mail. Einstein calculates these insights on an individual level which enables a marketer to focus on the strategic placement of those activities in journeys.
Those same insights are being used to calculate the frequency with which a customer should receive communications from within SFMC, all optimised via the Einstein Engagement Frequency activity. As a marketer you’re able to analyse the saturation of all contacts from undersaturated, on target, almost saturated and saturated and adapt the email frequency accordingly. Even if there would not be sufficient data on you as a subscriber, Einstein finds it way in suggesting the optimal frequency based on the general engagement of the contacts in your organisation. This means, you can implement those features already when they enter the first stages of the customer lifecycle.
The same counts for Einstein Send Time Optimization which basically generates an optimal send time score for each contact for each hour in a week. This feature enables a marketer to see in general:
The optimal send time per week or hour based on all contacts.
The subscriber’s predictive score calculated by Einstein per hour of the week.
The total number of contacts that are likely to open a message each day.
Depending on the nature of your campaign, time-sensitive or an always-on journey, Einstein STO is resolving all your problems with suggesting the best fit of time for a subscriber to send to. Increasing the send time window can give you additional insights for your strategy on high engagement segments.
Einstein Recommendations
It is so easy to present each customer with customised product and content recommendations throughout your various channels by the help of clicks with Einstein Recommendations and Recipes. When Personalization creates recommendations for your customers, ingredients define the parameters for considering items in your catalog. Personalization then weights those items according to your customers’ behaviors and affinities. Exclusions, inclusions, boosters, and variations help refine the recommendations.
The above features are all out-of-the box predictive capabilities of the Salesforce Marketing Cloud Engagement platform. Since last years’ Einstein 1 announcement, two generative AI capabilities were being added to the suite: Content Creation and Segment Creation.
Einstein Content Creation enables you to generate subject lines and body copy options for your emails and mobile messages. As a marketer you can configure the brand personality, and optionally enter a sample subject line or body copy to generate the best copy in line with your brand identity. If you use the third-party integration with Typeface, you can even AI-generate images to accompany your content.
A more innovating feature is the AI-generated Segment Creation which is now possible with Data Cloud for Marketing. Data Cloud was already providing an answer to building an advanced segment grounded in your data with clicks, no code – with this new feature you only need to describe an audience in a prompt and Einstein will generate it for you. As a marketer you’re able to co-create the segment after refining what Einstein suggested to you.
Create an audience similar to an existing one with Einstein Lookalike Modeling based on insights from your entire audience. This helps you focus on your high-value segments and create more of them. Discover here what other features Data Cloud have for marketers in their latest releases.
Assess your organisations’ AI readiness
The opportunities that are in front of us are immense but don’t need to be too complex. You can start creating use cases and build an actionable roadmap. As an organisation you need to identify and prioritise high value use cases.
Future-proof your personalisation game by letting us help you review the out-of-the-box AI capabilities. Together we can look for areas and processes that are inefficient or where customers could benefit from a better experience.
