Account-based roll-ups combine data from related records to give you a more holistic picture of an entire account, or company.
When you view all your data by account -- regardless of whether that data is generated from a CRM or any other cloud application -- there is a broad spectrum of reports at your fingertips, such as:
- Active Customers
- Contacts by Industry or Country
- Sales & Marketing Activities
- Active Marketing Opportunities
- Churn Rate
- Tickets & Account Customer Success Score
- High Value Customers Approaching Renewal
- And more
Data is spread across CRMs, marketing automation, support systems, ERPs, and other SaaS applications. CRMs contain data about companies, not tickets. Meanwhile, the support system will house data about tickets, not companies.
Value of Account-Based Roll-Ups
Account-based roll-ups provide you insights by aggregating data at an account or company level, so you can draw meaningful conclusions. When organized at an account level, data has more meaning than when it’s scattered across dozens, or even hundreds, of individual records on leads, tickets, or activities.
Rolling up ticket and company information by account is extremely valuable because it lets you understand an entire account’s support experience with your business. You could answer questions like:
- What is the average number of tickets per account per month?
- What are the Company and Contact properties for each ticket profile?
- What is your combined satisfaction rating?
- What is the average number of tickets or conversations for a new contact?
Account-based roll-ups are also beneficial for viewing data about leads by account. You could questions such as:
- How much have you invested in targeting a specific account?
- How much pipeline revenue was generated by that account per campaign?
- How many interactions were needed before the account was converted to a customer?
- What was the medium (e.g. phone, email, chat, etc.) for these interactions?
- What was the optimal sequence of interactions that most effectively led to the acquisition of a new customer?
As this is just a foretaste of what account-based roll-ups can do for you, let’s take a closer look at how Fusion gathers data from many sources.
Traditionally, to combine data from many sources so as to create a common, object-oriented schema would demand hours of data wrangling. You would need to extract data from multiple SaaS applications, eliminate duplicates, resolve conflicts, clean up format inconsistencies, join tables, and consult a range of BI tools and dashboards.
This task is especially onerous, as System A may contain the data for a certain field (e.g. Activities) but not be designed to report on that field as well as System B, which lacks that data. Such limitations snarl teams in complex migrations. Often they end up reporting out of System B account data from System A.
Fusion solves this by creating fused records. By joining objects on a common key, data from multiple systems system coalesces. If System A has null values for a certain field, System B can fill them, and vice versa. Any conflicts between the systems are resolved, the formats standardized, and duplicates eliminated. What this gives you is the chance to report on an account’s entire experience in any area.
Now let’s take a look at some real world examples.
Example 1 -- Rolling Up Support Activity by Account
At Bedrock Data, we use HelpScout for support, Salesforce for CRM and HubSpot for marketing automation. We can fuse data from all three applications to get a unified database, without getting mired in data prep.
All we’d do is access the company_ticket_links table, which fastens support cases to accounts, something neither system can do on its own.
Aggregating support cases at the account level is a huge win. Below you can see the average number of tickets per month and tickets per account, which signal to us which accounts might be more prone to churn based on their relative incident rates.
Example 2 -- Rolling Up Activities at an Account Level
It’s often useful to roll up activities at an account level to get a consolidated view of what’s contributing to a specific opportunity.
Below is a summary view of activities from HubSpot, Salesforce, and HelpScout, plus in-product engagement via Intercom.
When we talk about rolling up activity data, “activity” can mean a lot of different things. A user could have:
- Submitted a form
- Clicked an element
- Visited the pricing page on your website
- Clicked a link in a new product announcement email
- Requested a product demo
- Or downloaded a white paper
The power here is in aggregating these kinds of events -- from your Salesforce Activity History, from HubSpot events, or Interesting Moments in Marketo -- to view all activities for a single account. All based on data that isn’t naturally organized in the originating systems.
Example 3 -- Rolling Up Leads
Leads are “objects” which are not part of an account in a CRM. For this reason, marketers have struggled to get a clean picture of marketing and campaign activity at an account level.
Rolling up lead data on the account level gives you a more holistic view of your leads than if that data had stayed siloed across multiple systems. Rolling up leads at an account level will help you see the sequence of activities that led to a deal being created, across all individuals on that account. It will provide insight around the interdependencies between stakeholders on the account, and the sequence of activities that occured within the account leading up to an opportunity being created or a deal being won. You also can get a full picture of data across all systems, as you have access to all the meta-data across all systems. Here’s a visual of what that looks like:
Marketo Data: Salesforce data:
Getting started with rolling up account data is easy. Here’s how Fusion works in four connected steps:
1. Connect your data sources. Extract your data from SaaS applications such as Marketo, HubSpot, Salesforce and NetSuite. In just a few clicks.
2. Fuse your data. Automate data matching, de-duplicating, resolving data conflicts and modeling object relationships for more real-time reporting and dashboards.
3. Warehouse your data instantly. Automatically access your database via a cloud data warehouse.
4. Feed analytics & BI tools. Let your cloud data warehouse feed SQL input into tools you are using for visibility and analytics including Tableau, Microsoft PowerBI, Amazon QuickSight, MetaBase, and more.