The State of Marketing Analytics: Insights in the age of the customer

  • Rating: 
    5
  • Charts and Graphs: 31

There’s more data available than ever, and that’s exactly why it’s so challenging to truly make sense of marketing data. While cloud-based data platforms have accelerated the availability and access of marketing data, it hasn’t made the marketer’s job any easier. It’s just the opposite. ‘Mo’ data, mo’ problems.’


Enterprises are stuck between fragmented data silos through cloud providers. There’s customer data, inventory data, log data, search data, reporting, analytics, CRM, session data, et. al - with different vendors supporting each. While “real-time” customer data sounds nice in theory, the actual process of broadcasting this information through the organization is time-consuming, expensive, fragmented, and frustrating. It requires highly trained, expensive analysts generally doing analysis below the grade of their PhD’s. 

It’s an Excel-spreadsheet-in-your-inbox world, and we’re just living in it. 

That’s not to say there isn’t room for optimism. Both established vendors and the startup marketplace are gathering en masse around the following themes for to make data ultra-available and ultra-usable. You, the marketer, simply need to catch up.

  • Managed data: Fragmented data sets are driving rapid innovation in data management, storage, and access.
  • Distributed, contextual data: Organizations struggle with finding/delivering the right information, at the right time, in the right format, to the right audience. The data is there. The content and services are catching up. Marketer skills still lag significantly in this area, but there’s reason for optimism.

This report will answer:

  • The primary objectives for marketing analytics
  • Map the marketing analytics landscape across 10 key use cases:
  • Brand/social analytics
  • Customer insights/feedback/value analysis
  • Conversion and optimization
  • Mobile/app analytics
  • E-commerce
  • Ad effectiveness/advertising insights
  • Cross platform analytics/attribution modeling (may include tactical methods)
  • Machine learning/predictive analytics
  • Customer experience/call tracking/service analytics
  • SEO/SEM analytics
  • Outline the top vendors available for every use case
  • How marketers approach each use case, their primary roles, priorities, and satisfaction levels
  • Which areas vendors are meeting expectations or lagging
  • An overview of the massively complex marketing data ecosystem. We counted 800+ vendors in use across the 10 key marketing use cases listed above
  • Guidance for the types of advanced analysis your marketing organization needs to be investing in now to compete for customer relevance

___________________________________________________________________________________________________________

This report is incredibly impressive. It is head and shoulders above what I've seen from other research firms in terms of readability and overall experience. My team grasped the value of the marketing analytics report quickly and applied the data to inform some upcoming projects immediately!

Tim Wu - Director of Customer Growth; Framed

___________________________________________________________________________________________________________

Who this report is for:

  • Marketers:
    • Brand marketers, customer intelligence analysts, media managers, growth marketers, mobile marketers, campaign managers, marketing data managers and analysts
  • Vendors in the following categories:  
    • Brand marketing; audience insights; ad effectiveness; conversation rate optimization; mobile analytics; e-commerce providers; web and mobile analytics; cross-platform/attribution partners; customer experience and service vendors; search engine marketing partners; marketing data agencies

Methodology:

This report is comprised of a survey of over 1,000 marketing analytics professionals across 10 key marketing analytics data use cases; a review of hundreds of vendor-driven best practices documents; 3rd-party research from established firms; case studies; and dozens of interviews. 

Special thanks to:

Tableau
Ensighten
GoodData
Scopio
AirPR
Google
Yieldify
Ninja Metrics
Synthesio
Xavier University
Blueshift
Brightfunnel
Adobe
Beckon
Salesforce
Epsilon