Account-Based Analytics: Merging 3rd Party with 1st Party Data

We don’t want to discount the power of organizing your owned data assets from an account-prospective as there’s so much wealth to illuminate from this dark data for teams to view and use to optimize daily efforts.

However, do not discount the power of 3rd party data providers who can complement your account data. Below are some various vendors (some we use here at Dynamo). Take note also – there’s many industry and vertical specific providers that may have more depth than breadth. But in many cases, from what we find, both have value, it’s just applying the data in the right direction.

If anyone would like our POV– give us a shout anytime, we’ve researched and used many providers below (and more!). All providers have offerings with a combination of  B2B contact databases, social, news, firmographic and technographic data that can be applied to your account-based endeavors. All have data connecters through APIs that can be ingested within your internal or service provider tools to align to your target accounts.

  1. Clearbit (horizontal)
  2. Full Contact (horizontal)
  3. Leadership Directories (Vertical, government)
  4. Dun and Bradstreet (horizontal)
  5. Redbooks (Vertical, Advertising)
  6. Winmo (Vertical, Advertising)
  7. S&P Capital IQ (Vertical, Finance)
  8. Crunchbase (Vertical, Technology)
  9. Zoominfo (Horizontal)
  10. DiscoverOrg (Vertical, IT)

That’s the quick gist–as always, just trying to find right, not act right. Welcome feedback.

Team Dynamo.

Account-Based Analytics: Workforce optimization and alignment.

Human capital optimization is a key component of an Account-Based Analytics strategy for high performing B2B teams. This helps answer a couple key enterprise knowledge work questions such as:

  1. How do we align our B2B workforce toward the most wealth-driving activities?
  2. How do keep everyone on the same page at any moment?

An Account-based driven business believes the account is the common denominator for teams to apply effort and optimize toward (whether product, revenue or operations teams).  How and what should workers do to fight again “work drift.” Work drift happens when lots of work is happening, but not applying energy to the most wealth driving activities. If your account driven, the response is   – ok, which account should I work on? Advanced analytics help with the who and what, so knowledge workers are applying their resources effectively.

As more advanced technology takes over back-office tasks, Knowledge workers can now truly focus on the true wealth drivers of any business– Innovation, Commerce and Relationship Capital – these tenets can be aligned and optimized toward the account.

An account-based analytics strategy does exactly that. Data is organized in a way to constantly optimize workforce habits toward winning, keeping and growing accounts.

A great way for B2B firms to understand how their workforce is aligned by their accounts is to understand which work habits are aligned to your firms target accounts. There’s eight hours in each day – how many are devoted to the account? A firm who is adopting an account-based strategy, will want to continue to optimize toward more time toward target accounts, not less across all their knowledge worker’s functional roles.

Likewise, for firm’s who have not adopted an Account First approach yet, looked at the data from this prospective may enlighten how effort is being applied.

One insight module to take a snapshot to this answer this question is to showcase what folks are doing on a rolling 30-day basis relative to target accounts. For this exercise, we’ll use productivity software as a proxy for workforce efforts toward account.

For this account-based insight module, we will need below data:

  1. CRM
    1. Account contacts: email
  2. Email/productivity suite
    1. Email of employees
    2. Calendar and email event data

After obtaining the data, we’ll need to group and make all employee interaction relative from an account prospective.

At every interaction with email or calendar event with an account contact or if within the email, we can attribute content to account, we need to denote. Either one of two options.

  1. The account name
  2. or no account name, if unable to attribute.

Attributing action to the account can be based on if email chain has an account contact, email domain or a contextual analysis of the communication to see if internal email conversation is regarding the account. OK don’t want to go to deep with this post, hoping for review easiest directional setup.

At each interaction point, we can create a score to represent time (it’s cumbersome actually modeling the work day exclusively on time, so creating a weighted score will be a lower cost to value). Every email and every calendar event across your B2B work will be logged via account name or no account. We can create a score to tally interactions. For instance, emails will have a score of .25 meetings .75.

Now you can tally the score of all your accounts to have an “Account Effort Universe.” If your total score ends up being 100, at one of your target account equals 10, then 10% of your effort is going to that account. Since data represents out of 100, we can make a simple piechart to depict.

Likewise, for the “No account” label, you can review how much time is not directed toward accounts at all. Now, from your BI tool, business users can drill in and see what the data drivers are and associate to other firm wide KPIs (such as pipeline growth, revenue growth, product usage) to understand action to outcome.

Firms may quickly understand the effort applied to the wrong accounts and may want to redirect to other advantageous accounts. Further, at the individual level, workers can double check their daily work exhaust to ensure they are spending their time wisely.  We have another post on applying the “outcome” to your account effort here.

As always, we’re not trying to act right, just find right, would love to hear thoughts.

Team Dynamo