Account-based marketing (ABM) is red hot right now for B2B—because it works. In ITSMA's 2017 Benchmark Report, 87% of companies agreed that account-based marketing gives a higher ROI than other marketing activities, and 69% of respondents saw improvement in average revenue per strategic account when using ABM.
Account-based marketing, in a nutshell
Account-based marketing means marketing to a set of accounts that fit an ideal customer profile (ICP), based on the common traits of previous and existing customers. These common traits can be identified by your sales team and by examining and comparing data points in your CRM.
To successfully identify an ideal customer's traits, your CRM must contain quality data.
What is quality data?
Correct: ensures a field's value is the real value
Incorrect field: Company Name [Goggle]
Correct field: Company Name [Google]
Complete: ensures as many fields as possible are filled
Incomplete fields: Company Name, Revenue, Address
Complete fields: Company Name, URL, Industry, Revenue, Headcount, Address, ...
Unique: ensures there are no overlapping entities
Duplicate entities: [Google, $31B, 1600 Amphitheatre Parkway] [Goggle, $31B, 1600 Amphitheatre Parkway]
[Google, $27B, blank]
Unique entity: [Google, $31B, 1600 Amphitheatre Parkway]
It can be difficult to ensure a CRM contains quality data when data is entered manually, records aren't filled to the best of their abilities, or a record contains out-of-date data.
As the computer science idiom goes, "garbage in, garbage out"—flawed inputs can only produce flawed outputs.
What are the effects of flawed output from an account-based model?
Identifying a prospect that is unlikely to convert --> wasted resources
Not identifying a high-value prospect --> missed revenue
Incorrect marketing strategy used on accounts due to poor prioritization --> wasted resources and fewer conversions
Incorrect inputs to your account-based model waste resources and lose prospects, as well as revenue.
It can be very difficult to identify when outputs are actually flawed. Instead, ensure that your inputs are as correct as possible—your ICP traits. That means you need quality data in your CRM.
One of the downfalls of traditional CRM systems, such as Salesforce, is that when doing account-based marketing they use a lead-based data model. Lead-based marketing concentrates on an individual, whereas account-based marketing concentrates on companies, which have 0 to many contacts.
Quality data for account-based marketing means correct, complete and unique CRM data that focuses on companies rather than individuals. In short, there is no "Lead" in account-based marketing.
Let's say you're in a relatively good spot and have a lot of the standard Account fields filled out (Company Name, Phone, Website, Industry, Employees, Annual Revenue, Description, Billing Address). With this, you can only craft a very rudimentary ideal customer profile—likely based on industry, company size, and location.
This data is incomplete for meaningful account-based marketing—there aren't enough data points to create a robust ideal customer profile. To create a more complete picture of the company, you should add in more data points relevant to your business.
If you're in ecommerce, you might care about vendor volume, monthly web traffic, and technologies used. If you're in the cybersecurity industry, you might care about hosting services used, security certifications, or a recent data breach. Make sure all relevant fields are filled out on all account records before running an ICP analysis to inform your account-based marketing.
You can check for correctness by:
Having strict input rules for each record
Standardize data entry so that new records have required fields filled out (and in a certain way) before being added to your CRM
Traverse lists of records and update information manually
Sync records with robust third-party datasets (like Oracle Datafox) to keep records up-to-date
Do you know all the ins and outs of ABM? Find out what you might be missing with the "Account-Based Marketing Handbook."