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: Systems of engagement

It’s true. The BI industry still has a huge adoption rate issue (https://bi-survey.com/bi-deployment).  So how can we align our workforce from an account-based prospective? Even if we have all the data now, and we can group and provide advanced analytics – who cares if no one is engaging with the insights?

As systems of intelligence advance in the enterprise, as Jerry Chen, of Greylock Partners, notes in this post,  https://news.greylock.com/the-new-moats-53f61aeac2d9, old and new systems of engagement must align to generate value.

At any rate, systems of intelligence need to interact with knowledge workers to drive action. Not all systems of intelligence will interact with your workforce directly (some may be focused on machine to machine interaction), but for the ones that do, there needs to be an almost zero cost to value for your knowledge workers to understand how it works and to derive insights.

At Dynamo, we breakdown systems of engagement in two prongs for knowledge worker interaction to increase adoption.

  1. Analysis automation – there needs to be a near zero cost to value for the vast majority knowledge workers to ascertain the insights. We believe insights that were derived from various data mining and advanced analytic techniques need to be generated in natural language for highest adoption rate.
  2. Accessibility – there needs to be a near zero cost to value for knowledge workers to rapidly leverage insights. All insights need to be available where your work force already works, do not add in another system for your workforce to learn. Unless there’s such an enormous value to beat the cost to value.

That’s it – there’s plenty of systems your workforce uses already. When evaluating new providers, make sure they seamlessly work with your existing workflows for highest success rates and knowledge is given in natural language within those apps.

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

Team Dynamo.

Account-Based Analytics: Relationship engagement depth and breadth

Revenue teams of B2B firms selling complex high ticket items may want to know how they are trending on penetrating various roles and constituents in their named accounts. It could be an account you are prospecting or current customer you are navigating for cross-selling purposes.

Engaging with and coordinating your efforts with a “relationship map” is a way to measure progress to help optimize those efforts alongside your larger account-based strategy. This analysis can be done with most BI tools as long as you can access the data. Below is a “quick general guide” to apply to your business data.

For this insight module, below data is needed:

  1. Account Contacts: Names, titles, phone numbers, emails of you target account.
  2. Account Engagement: You’ll need enterprise communication software, CRM, marketing automation.

Grouping the Data (develop a direct weighted score to measure impact, adjust weights as you see fit):

  1. Breadth
    1. Determine each touch point with an engagement score
      1. Meeting=.5
      2. Marketing=.05
      3. Email=.15
      4. Phone call=.3
  1. Depth
    1. Measure by time lapsed weight
      1. Within five days = .5
      2. Within 6-10 days=.2
      3. Within 10-30 days=.15
      4. Within 30-60 days=.1
      5. 60+ = .05

Factoring the Score

  1. At each channel touch point multiple weighted time to engagement score, this equates to a unique point tally per account.
  2. Normalize for each account. Divide engagement score by total contacts on your list. This gives a time-weighted engagement ratio. (this method unique per account, higher the score the better)
  3. Consolidate data into a tree map (or other visual to quickly see weighted output).

From this high-level vantage, business users can ascertain which accounts need reinforcement and/or deeper dive. Score below 100 should be a red flag to dig in more(in above example, accounts in lower right hand corner, like Metlife).  Also, it’s great to compare growth or stagnation by looking at a snapshot today compared to 30/60/90 days ago.

After determining health, great tools in the market to help fill your relationship gaps. We will give a shout out to www.reachable.com, a great for enterprise B2B firms to leverage their existing relationships for referrals into target accounts.

As always, we’re not trying to act right, just find right, would love to hear thoughts on different approaches to determining relationship depth and breadth into target accounts.

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

Account-Based Analytics: What is it and what’s the point?

Account-based analytics is a B2B data strategy that aligns internal and external information to measure and optimize business impact from a target account prospective. B2B firms are rapidly infusing the “account-based” centric model across functions including marketing, sales and customer success to align knowledge worker’s efforts to win, keep and grow their best accounts. Account-Based analytics is a method to measure and optimize those efforts cohesively.

This makes total sense to Dynamo, B2B firms should build and serve their accounts (not from an individualistic/B2C prospective).  The account-based mantra is not stopping at the revenue half of the enterprise, other functional areas such as finance and operations and can align their efforts to firm’s target accounts for all knowledge workers to think account first.

As such, firms adopting an account-based approach to their B2B endeavors need an analytics stack and practice to measure and optimize performance from this prospective every day. Dynamo believes Account-Based Analytics will continue to rapidly transplant and complement traditional B2B data strategies with the overall arching mission to align workforce activities to win, keep and grow their best accounts.

Is the idea of serving our account the best we can a new idea, absolutely not! But, the technology and tools now available have made it much more attainable to truly deliver this promise to every knowledge worker operating in a B2B firm in a seamless intuitive way. We’re excited to share everything we know and are working on within the emerging Account-Based Analytics landscape and happy to be a part of the puzzle with Dynamo’s on-demand account briefing service for B2B teams.

As alway we’re just trying to find right, not act right. Let us know your thoughts.

Team Dynamo