Salesforce is rolling out new features to its Marketing Cloud this week, leveraging machine learning and data science to add real-time predictive customer scoring and audience segmentation. Here are the details.
One of the big drivers in business analytics recently is the need to put insights directly into the hands — or onto the desktops — of business users who need them to make the best decisions to convert customers. The goal is to close the gap between the analytics pros who can create predictive models and the business users who know the right questions to ask and will use the information.
Salesforce‘s (CRM) new release Wednesday brought organizations closer to that goal.
The online customer relationship management (CRM) platform is announcing new analytics functions within the Salesforce Marketing Cloud that can help organizations by leveraging machine learning and data science to score and segment customers in real-time. This lets marketers provide each individual customer with the right campaign at the right time to increase engagement, Leslie Fine, Salesforce product VP for data and analytics, told InformationWeek in an interview.
Salesforce is providing these new features by baking predictive analytics directly into a new offering called Marketing Cloud Predictive Journey that includes two capabilities — Predictive Scores and Predictive Audiences.
The idea is to take marketing analytics into a new era in the same way that consumer maps and navigation have entered a new era. We don’t consult paper maps anymore, Fine said. Gone are the days when we’d go online to use a website to map our route and then print out that map so we could refer to it later, because the minute you print that map, the information is stale, she said.
That’s similar to what’s been going on with marketing analytics. Marketers get reports with information about what is going on in the business and with customers, but it is up to those marketers to decide what to do with it. The information is out of date as soon as the report is produced.
New map and navigation applications such as Waze and Google Maps adjust their recommendations based on real-time information, and if you decide not to follow the recommendations of these apps, they adjust their behavior according to your decisions, not the other way around, Fine said. Salesforce’s new capabilities are bringing that kind of predictive and responsive model to marketing analytics.
“That’s what a predictive journey is. It’s all about letting the marketer accept the goal to drive the agenda and using the data to inform that and automate it for you,” she said. “This is all about driving smarter customer engagement in a way that is super simple for the average marketer.”
The software does this with two sets of features. First, the Predictive Score applies machine learning and data science to each customer, making predictions on how likely that person is to open an email, click on an offer, unsubscribe from the mailing list, or make a purchase. Based on that, each customer is assigned a score.
[Salesforce has been upping its analytics game. Read Salesforce Drives Analytics Deeper Into Sales Process.]
For marketers who want to go deeper, Salesforce’s Predictive Score enables views into what makes customers likely or unlikely to buy. Some of those metrics might include, for instance, whether the customer uses an iOS device, has downloaded a retailer’s app, has abandoned a shopping cart, or has visited the website in the last week.
These scores are integrated into Salesforce’s Audience Builder. Then the second new feature, Predictive Audience, enables dynamic segmentation of the audience. For instance, Fine said, marketers can now send one campaign to a segment of people who are very likely to engage, and send a different campaign with a coupon to those who have been rated as having a low likelihood of engagement. Perhaps another segment of the audience will receive a less frequent cadence of email offers.
Every day each customer is rescored and dynamically re-segmented, based on their engagement at various touch points, including their response to the campaigns, Fine said.
“These features are the beginning of how we think about predictive journeys,” she said.
Michael Fauscette, IDC group VP for software applications research told InformationWeek that these new features are a big deal to existing users of the Salesforce Marketing Cloud, particularly to those who are already using the Journey Builder tool. Journey Builder helps organizations take a deeper look at the customer process of research and engagement before those customers actually make a purchase or abandon the process.
Adding Predictive Journeys with Predictive Scores and Predictive Audiences adds several data streams to the mix, providing organizations with a much clearer picture of the best way to approach the customer at that moment in time.
“All the marketing organizations I talk with are trying to find ways to interact with prospects and customers earlier in the decision process, optimize any opportunity to interact by being contextual and relevant, and provide the right educational content at the right time,” Fauscette said. By providing what the customer wants at the right time, organizations “increase the probability of providing a positive customer experience, while increasing the likelihood of a revenue event.”
These new features within the Salesforce Marketing Cloud are currently in beta testing. They will be available to customers of the Salesforce Marketing Cloud Enterprise edition and as add-ons to the Pro and Corporate editions.
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Jessica Davis has spent a career covering the intersection of business and technology at titles including IDG’s Infoworld, Ziff Davis Enterprise’s eWeek and Channel Insider, and Penton Technology’s MSPmentor. She’s passionate about the practical use of business intelligence, … View Full Bio