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Experienced marketing technologists know that martech isn't as simple as finding an "easy button" you can press and automatically get more leads and higher conversion.

They know that if you feed your technology garbage, you'll get garbage out the other end. And they know that data quality is the foundation for it all. And attribution is a great example of why that's the case.

But for successful and scalable attribution, high-quality data is just the beginning. Let's look at three issues people often trip over when employing attribution technology.

1. Flexibility to Scale

Attribution is conceptually simple—just a bit of data tracing, counting, adding, and dividing. What makes attribution difficult is not the fancy models, but whether you can easily make it work with your systems, data, and processes.

Here are three technology constraints common to attribution solutions.

Salesforce or Bust

All attribution solutions work with Salesforce data. A few work with Marketo. But beyond that you're looking at writing custom Python code.

New martech solutions and vendors are still emerging rapidly, so you need the ability to ingest engagement data from a broad range of sources, including...

  • CRM (beyond Salesforce)
  • Marketing automation (beyond Marketo)
  • Data warehouses and databases
  • Sales engagement tools such as Salesloft and
  • Sales insight tools such as Gong and
  • Revenue insight tools such as and Clari
  • Intent data such as G2 and Bombora
  • Your own product's free trial and freemium activity
  • Data from your channel partner

Incorrect Salesforce Setup

Even if most of your engagement data is in Salesforce, most attribution solutions assume your instance is set up generically and you're using objects such as Lead, Contact, Account, and Campaign Memberships in "standard" ways.

But if your Salesforce instance is more than five years old and you're a large company, it's never that simple. To make it work against such rigid technology constraints, you resort to doing things that make your Salesforce even more messy.

One large technology company we worked with wanted to incorporate sales meetings into its attribution model, but its tool worked only with the Campaign Membership object. So, it bulk-created a campaign for every day of the year and wrote code to match all the sales meeting data into those daily campaigns. When the project went live, team members had added over a thousand new daily campaigns to their instance.

Custom Object? What Custom Object?

Custom objects are a fact of life unless your Salesforce instance is less than three months old. They capture critical data that's specific to your company's go-to-market motion. Most attribution tools have limited, if any, ability to deal with custom objects.

One company used a custom object to capture data on its channel sales and partner influence data. Unfortunately, the attribution tool it deployed years ago didn't support custom objects, which required additional manual work and ultimately delivered the combined data into a data warehouse and used Tableau for reporting.

The company recently replaced the manual work with an integrated RevOps automation platform. Its next step: using that platform to replace the entire attribution solution.

2. Flexibility to Model

If there's any martech topic that evokes religion-like fervor, it's the attribution model. People will debate—until the cows come home—which attribution model is better and more accurate .

Every model is flawed, yet every model can provide insight. You need to run multiple attribution models because each model answers a different question.

Which campaign is best at...

  • Sourcing new leads?
  • Nurturing leads?
  • Growing upsell and cross-sell business?
  • Closing new business?
  • Turning one-way outreach into two-way conversations?

From there, you can determine...

  • What pattern of touches creates the largest deals?
  • What's the buyer's journey for a specific type of market segment?
  • Which type of deal is Marketing vs. Sales best at sourcing?

No single attribution model can answer more than one or two questions. So, you'll need to run different models to answer different questions for different stakeholders.

Your attribution solution should enable you to run as many models in parallel as you need, and customize the models to fit your exact business logic.

3. The Flexibility to Tell Different Stories

Attribution shouldn't be a tool for Marketing to justify its existence and show management how many opportunities it has created for Sales—or, worse, used as a tool to argue with Sales about who should get the credit for business.

Attribution helps answer questions about what works and what doesn't for different stakeholders. For example:

  • Marketing wants to know which content syndication vendor generates the highest-quality leads.
  • Sales wants to know which in-person event format generates the highest engagement.
  • Demand Gen wants to know what nurturing pattern generates the shortest buying cycle.
  • The CRO wants to know how senior buyer personas' engagement in deals affect the size of the deal.
  • The CMO wants to know the impacts of key brand-building campaigns.

To effectively use attribution analysis to answer all those questions, you need the ability both to run different models and to present the data in the most straightforward way to each stakeholder.

Most companies use additional custom analytics and reports, requiring the use of a data warehouse and data visualization tools. It would be ideal for the attribution tool to have the flexibility to generate targeted analysis for specific stakeholders without those additional steps.

One way to accomplish that is with a RevOps automation platform that enables the attribution project team to create customer applications that deliver data and visualization for teams in various departments and regions.

Your Attribution Solution Should Grow With You

Attribution offers powerful analysis when done correctly. To have an attribution technology that can accommodate your business needs, keep up with constant changes, and service the needs of many stakeholders, select a platform that not only meets your needs today but also scales with your company as your use of attribution analysis becomes more mature and widespread within your organization.

More Resources on Marketing Attribution

Four Steps for Successfully Implementing Marketing Attribution

Attributing Conversions to Campaigns: What Can Attribution Do for Your Marketing?'

How to Improve Marketing Attribution Without Burdening Your Sales Team

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image of Ed King

Ed King is the founder and CEO of Openprise, a data orchestration SaaS company. He has over 20 years of experience in enterprise software.

Twitter: @ekwking

LinkedIn: Ed King