Customer Data & Analytics Blog

This Is Why Your B2B Data Driven Marketing Doesn’t Work and How AI Can Fix It

Abhi Yadav | 2 minute read

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No doubt, Account Based Marketing (ABM) is a big priority, thanks to modern AdTech companies, who have championed this. However, advances in data & AI technologies have made it possible for Marketing Operations to plan everything from an Account Based perspective. Despite this, many marketers still struggle with the challenges of data quality, fragmented reporting and sheer volume of martech stack silos. 

If you recognize the following challenges, you are not alone:

  1. Data quality challenges within target accounts
  2. Trouble with ongoing target persona discovery due to varying job titles across accounts and industries
  3. Contact information is not up to date or complete
  4. Account information is static
  5. Third party lists have huge overlap and incremental information is missing
  6. Data enrichment is not continuous given the volatility of B2B data
  7. Leads are not mapped to existing account information within CRM
  8. Accounts have huge de-duplication & incomplete information 

What can B2B Marketing Operations do?

  1. Identify the target account(s) as per TAM (target addressable market) across geographies  
  2. Identify the target persona to relevant product category, well beyond the Job function and title
  3. Set up a dedicated system for TAM data, like a Dynamic Database Management System to sync data from CRM & Marketing Automation and unify all data of target account(s), without IT dependency
  4. Continuously update & enrich target account information on an ongoing basis
  5. Update target accounts with current installed base information, or technographics, or firmographics easily with third party sources
  6. Capture ongoing web signals of target accounts and power business triggers within TAM accounts
  7. Leverage predictive analytics to prioritize call to actions within entire TAM accounts on a weekly/monthly basis
  8. Track business triggers and account intelligence on an ongoing basis for relevant calls to action
  9. Leverage marketing automation with relevant content orchestration across personas, business triggers, and opportunity stages.
  10. Trigger individualized 1:1 promotions and content marketing for continuous lead nurturing in target account and personas 

How AI can play a key role in ensuring the above:

  1. Unifying target account information across silos while removing over traditional challenges for eg. know W Fargo = Wells Fargo or Matt Hurley & Matthew Hurley is same, despite the different spelling
  2. Ongoing data appending and enrichment – contact information, job title, persona info etc.
  3. Target persona discovery in target accounts, with reference to their media consumption, digital behavior etc.
  4. Ongoing web signals relevant for your business. i.e Job listing, announcement, merger & acquisition etc.
  5. Automated machine learning based predictive analytics for ongoing account opportunity scores and other relevant dynamic metrics like Buzz score, Growth score etc.
  6. Graphical view enabling Account 360 view with more than just parent-child linkages of accounts, but with contact mapping, technographics etc.

Zylotech has been helping some of the world’s biggest B2B marketing operations teams–not not just by making their customer or target account data updated and consumable, but by helping them monetize their target customer data without the frustration and challenges of maintaining data quality. 

AI powered Account Intelligence while integrating with your CRM and Marketing Automation system not just ensure continuous data quality, but also ensure very deeper account insights and predictive analytics metrics to ensure very effective marketing and sales operations.

Topics: Customer Intelligence