Use ClearGraph to: Target Higher Paying Accounts
Original post written by Andrew Vigneault on August 27, 2015.
ClearGraph connects directly to customer relationship management services like Salesforce, Base CRM, and Pipedrive to help you better understand your customer. In this blog post I’ll demonstrate how to target deals that will yield the largest account values, so you can best leverage your sales team’s efforts.
1. Connect my CRM to ClearGraph
I’ll begin by connecting my CRM to ClearGraph, I’ll use Salesforce for this example. Integrating Salesforce takes less than 10 seconds, and once the data has loaded, I’m ready to start asking questions.
Which industries drive the highest account value?
Once Salesforce is connected, I will to start by evaluating which industries drive the highest account value. I can achieve this by searching “Average annual revenue of accounts grouped by industry”. This search gives me a scatter visualization that shows the relationship between industry and annual revenue. I can see which are the highest value industries without getting hung up on outliers and low volume accounts which shouldn’t be included in my analysis. Before moving on, I will create a new collection, name it “Source High Paying Accounts”, and save this visualization in it so I can easily get back to it later.
What are the sources of the most valuable industries’ accounts?
With our scatter analysis we can see the Energy industry has a healthy number of accounts and are also on average our highest paying. We may want to focus on driving new Energy accounts. Banking and Retail also seem to be high value industries. I’d like to better understand where accounts for these industries are coming from to see if there’s a way to focus on those deal sources. I’ll start by drilling down into the Energy industry. We can do this with the drill down feature by clicking on the Energy data point to get a number of drill down options including type, source, location and more.
We use many channels to drive new accounts so I have drilled down into source. This is great because I can see the majority of Energy accounts are sourced through purchased lists followed by phone inquiry and then the web. I will save this to the collection I made for the prior visualization. I happen to know that we haven’t purchased a leads list in a while so it may be time to revisit that strategy!
Where in the world are my accounts located?
I need to break down purchasing by geographic location so that I know where in the world the accounts are coming from. We can regroup the data by manipulating the question to “Total accounts whose industry is ‘energy’ grouped by source and state”. When we regroup the data it is obvious the majority of the energy deals that come through our purchased list channel are from Texas and California. This is great, now when we purchase a list we will be sure to specify the leads are from both California and Texas.
2. Create an email report
I will save this last visualization in the collection too. The collections are dynamic and will update in real time. I will set an automatic email report that emails me this collection on the first Monday of every month. I will use that email report to stay on top of changing trends to continuously ensure we are allocating our sales efforts in industries and channels that have the highest ROI.
