Power Einstein Prediction Builder With CX data

Understand the importance of pulling in customer feedback for data analysis and how to harness the power of Einstein Prediction Builder.


Sara Staffaroni

March 12, 2020

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We launched the GetFeedback integration for Salesforce way back in 2014. Since then, we’ve been constantly inspired by how our customers have used the integration to power their customer feedback programs. 

One thing we’ve learned from some of our most innovative customers is that when survey data is integrated with Salesforce, it can help augment your customer data to better fuel Einstein Prediction Builder. 

We want to share with you the secrets to using GetFeedback data to power Salesforce’s artificial intelligence platform called Einstein. By the end of this article, you’ll understand the importance of pulling in customer feedback for data analysis and how to harness the power of Einstein Prediction Builder in your own organization.

With Einstein, we have the intelligence to work smarter

Einstein is the AI available in your Salesforce CRM. It learns from your existing customer data and gives you predictions and insights about what your customers really want. It can deliver the next steps and recommendations that help to personalize your customer experience without requiring any code. 

When it comes to improving how our organizations connect with their customers, there’s tremendous value in bringing the power of AI into Salesforce to supercharge business processes. Einstein allows Salesforce customers to work smarter and make decisions faster. Some ways that customers are already using Einstein include: 

  • Building AI-powered predictions and recommendations on which customers are at-risk and who to focus on. 

  • Embedding actionable insights directly onto Salesforce customer records to address issues and course-correct.

  • Operationalizing AI with intelligent workflows and business processes to escalate issues to the right teams.

But predictions are only as good as your data

Einstein can only use the data available to it to make predictions. As the old saying goes – garbage in, garbage out. Businesses can’t build a full picture of their customers if they don’t have enough good data to power their analytics engine.

And it’s a common problem: in a recent survey of nearly 900 Salesforce admins, Cloudlingo found that over half of respondents blame poor data quality and a lack of data collection as to the main reasons for not having a 360-degree view of their customer.

Bad data can happen for a variety of reasons. From data entry issues to insufficient data to biased surveying—your database can be compromised in many ways. Every error can skew Einstein’s prediction model. 

One way to improve your data integrity is by automating the flow of data from your customer surveys into Salesforce. Most teams store a ton of data from other systems but what about from the customers themselves? How can we build the right model to help us predict customer behavior without using direct customer feedback?

Bringing customer feedback into Salesforce is the key

This is why customer feedback must be part of your data strategy. Leveraging the latest and greatest technology like Einstein Prediction Builder requires bringing in the right data. And to help prevent customer churn or attrition, customer feedback is a key piece of that data set. 

Einstein, Salesforce’s artificial intelligence offering, makes things like intelligent case routing and assignment decisions based on all your customer data in Salesforce. By giving Einstein visibility into metrics like customer satisfaction and agent performance, GetFeedback makes Einstein’s predictive functionality even smarter.

For example, Einstein can move an unhappy VIP customer to the top of your support queue. And an agent who always gets perfect CSAT scores for a particular topic can get those future cases routed to her automatically.

Leveraging integrated surveys can improve Salesforce data quality

So let’s break it down, how do you actually get customer feedback into Salesforce so it feeds into Prediction Builder? 

First, you use integrated surveys to capture customer feedback. Many of you might already have key metrics like CSAT, NPS, or CES that you’re capturing. Based on what workflows you want to use Einstein Prediction Builder for, those surveys might work, or you can use specific surveys to understand deeper levels of direct feedback. 

Leveraging integrated surveys can improve Salesforce data quality

Next, you’ll want to map the customer feedback from your surveys into standard or custom fields in Salesforce. GetFeedback’s integration allows you to do this through point and click—no code required. Simply choose where you want to put the data; on the contact record, account record, or maybe a custom object. 

Finally, use those freshly filled fields when you build your prediction to influence the end result. Einstein’s Prediction Builder is great for every department because you don’t need to know how to code to get results. 

Use GetFeedback data with Einstein Prediction Builder for more actionable insights

To understand what your customers are going to do next, you need to have a full picture of where they are now. That means collecting as much customer feedback as you can, in order to create an accurate prediction model. 

GetFeedback and Salesforce are perfectly paired to give your organization insight into building amazing customer experience. When you use GetFeedback to collect survey responses, it’s simple to use that data in your Salesforce workflows. From prioritizing customer inquiries to spotting at-risk customers to personalizing ongoing marketing initiatives, the customer experience is better when it’s driven by data. 

Get started with GetFeedback for Salesforce by following along in our new guide: How to run a successful CX program with Salesforce.

Learn how GetFeedback can help you exceed customers’ expectations—start your free trial today.

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