3 Reasons for Data Blending with Rekener

Build great 360 degree customer relationships by blending data from go-to-market systems with Rekener

Build 360 Degree Customer Relationships  

There are many benefits of a 360 degree customer view when it comes to winning deals and building relationships with customers over a long period of time. To prioritize accounts to target for net new sales, it's helpful to blend Salesforce data with marketing automation data. This shows which accounts are responding to marketing campaigns by opening emails, visiting web pages or downloading content.  By blending product usage data with Salesforce data, account managers can identify opportunities for expansion, and product managers can derive insights about what works best for customers. Customer success teams blend support data with Salesforce data in order to assess the health of accounts and identify churn risks. 

In order to have a 360 degree view of customers, we need to be able to blend data from Salesforce with data from other systems.  Data blending makes it possible to break down silos between different parts of the business, and surround the customer in a way that serves them best. 

So, if you're trying to get your sales, marketing and success teams aligned around a 360 degree understanding of your customers, here are three reasons to explain why it's worth the investment to blend data from your go-to-market systems. 

1. Data Blending at the Account Level

A true 360 degree view of customers and prospects means we need to be able to blend data from multiple sources at the account level.  

Why is this difficult?  The first reason is that accounts in Salesforce are often very messy.  There can be duplicates, and accounts with multiple sub-accounts including companies with different names that are part of the same corporate structure. The second reason is that the Salesforce data structure is complex. In Salesforce, it's challenging to roll up data that's hidden in line items or objects that are one or more levels removed from the account.

Rekener solves this problem with machine learning technology that recognizes duplicates and identifies hidden relationships between accounts, even if the account names are totally different.  Using this technology, Rekener creates account rollups.  With account rollups, it's possible to see all the data from different Salesforce objects at the account level.  For example, the number of leads at each accounts, product data by account, activities by account, etc.  It's also possible to join data from different systems, such as marketing automation, support and usage tracking platforms, and see all of this information at the account level.

With account rollups and data blending at the account level, you can do many powerful things.  Finding net new targets using multi-variable filtering is a great example.  Here's an illustration showing how to build a filter in Rekener that automatically finds accounts that are in a target vertical (finance) and have not yet purchased any products but are actively visiting the web page and opening marketing emails.  We call these "heartbeat" accounts, and they should be at the top of the sales team's priority list.

Multi-variable filtering in Rekener Account Control Center

2. "Pivoting" Data by Different Attributes

Another benefit of rolling up data to the account level is that data from different systems can be analyzed based on different variables, such as products, opportunities, sales teams, sales reps or even marketing campaigns.  This is a similar concept to pivot tables in a spreadsheet, and it is extremely powerful when data is blended from different systems.  

With the Account Control Center, Rekener's customers have used this functionality to do lots of really valuable stuff.  One customer wanted to analyze the effectiveness of marketing campaigns by comparing metrics from their marketing automation system, such as web visits and email open rates, side by side with metrics from Salesforce, like demos and opportunities generated. 

Pivoting on products is another powerful capability, especially for finding patterns for how customers have purchased products over time.  In one customer example, the historical data showed that close rates and average contract value were optimized when product "A" was sold to customers that already had product "G."  Once this cross-sell strategy was figured out, filters using data blended from multiple systems were used in order to find target leads and accounts to feed to the sales team. 

Here's an illustration of a filter in Rekener that finds accounts that have active subscriptions of one product ("G") but have not yet purchased product "A" and who are visiting landing pages for product "A."  This filter results in a list of accounts with a strong cross-sell heartbeat.

Finding cross-sell targets with Salesforce and Hubspot data

3. Adding the Time Dimension

Blending data from different sources can create even more valuable insights when you can see how the data trends over time.  We speak with Ops people all the time who are combining data from usage tracking tools or support systems into Salesforce.  The problem is that the data in Salesforce is a single data point, or a cumulative number, that is static and gets over-written every time the data is synced.  This loses the value of how the data has changed over time.

In the Account Control Center, Rekener's customers are able to see all of this data in time series.  Here's a graph that combines data from Hubspot and Salesforce that tells a powerful story of how this account has grown over time. 

Salesforce and Hubspot data in time series  

Interested in learning more?  Here are some things you can do right now:

 

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Alex Laats

Alex is CEO and Founder of Rekener. Previously, he served as President and COO at ZeroTurnaround and as President of the Delta Division of BBN Technologies. At ZeroTurnaround, he grew high velocity inside sales by 6x in 3 years. At BBN, Alex co-founded RAMP and AVOKE, both recurring SaaS businesses based on BBN's world class speech recognition and natural language processing tech. Alex started his entrepreneurial career as founder and COO of NBX Corporation, which led the transformation of business telephone systems to Voice over IP. Alex’s companies have generated $500M in liquidity events and more than $1B in sales.

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