“At our board meetings, marketing is always trying to show their value. I wish they’d just give up and accept they’re an expense.”
CEO of a large manufacturer
Ouch! That’s rough. At management meetings dominated by engineering and sales, marketing executives must demonstrate—with hard and credible data—that their investments have a positive return.
Building a marketing tech stack is expensive and time-consuming. The hype around sales enablement promised to boost revenue, but that’s faded to weak justifications such as “we need it to stay competitive” or “the salespeople love it…”
Intuitively, providing tools to salespeople when they need them makes sense but knowing if they make a difference is essential. “Loving it” is not a metric for success. It’s barely a reason to renew the annual license of the tools you already use. You need data to prove real value.
Even if you’ve integrated your CRM, marketing automation, sales enablement, and LMS, you still have a data problem.
Questions remain:
What marketing assets contribute most to closed won deals?
How and when do our best salespeople and dealers use our marketing assets?
How does training affect sales and dealer success?
Which marketing campaigns are most highly correlated to sales success?
Is your CRM really a source of truth? How do you fill in the gaps?
How much of your spend contributes to marketing ROI?
Marketing’s big problem is that data is dispersed, disconnected, and inaccessible.
According to IDC, 90% of organizations cite data siloes as challenging to growth. Typically, each department has its own siloed data which causes many problems.
Some of the big ones are:
Lack of transparency
Data duplication
Inability to act on data
Fractured customer experience
Lack of trust in data
Other problems are the increased manual work, hindrance of reporting capabilities, lack of visibility into ROI, and increased barriers to privacy compliance. Overall, siloed data reinforces operational and functional siloes.
If your organization is like most others, these data silos have grown over time and become more isolated.
Some organizations have turned to data warehouses to organize siloed data into tables for SQL queries. SQL-based data warehouses are a great tool for surface-level reports.
However, if most of your relevant insights are journey-related, as in customer journey, sales cycle, or product life cycle, SQL-based data warehouses are limiting. They’re not built to traverse these paths to uncover meaningful insights into the above questions.
Why Marketers are Turning to AI to Solve Data Problems
A recent Martech webinar hosted by Scott Brinker and Frans Riemersma highlighted trends in marketing technology. The use of AI was showcased in the following diagram:
There’s definitely growing momentum to apply AI in solving the core challenges of marketing ROI. Fortunately, knowledge graphs provide the missing link.
For more information on how to use knowledge graphs to drive value for marketing, check out Knowledge Graphs are Marketing’s New Superpower and the other videos and articles on our Resources Page
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