“If it’s not in Salesforce, it didn’t happen.”
It’s a fine slogan for a VP of sales, but it’s an outlook that should never be adopted by a CMO or CEO. The rest of the organization (product development, operations, finance, customer success, etc.) already knows better.
Organizations need an array of applications to run their business, and it isn’t always practical to purchase tools that try to do it all. Digital marketing is evolving too quickly to rely on a single tool across multiple channels. Because we must diversify our applications and these applications think of data differently than primary business applications, it isn’t practical to expect departments to exclusively report out of a CRM.
We Need to Talk…
Get comfortable because we’re about to talk through some #HardTruths.
The necessities of a single source of truth and data-driven decision making are never going to go away. What needs to change is the attitude around investing in analytics, and it must happen from the top down.
In the 2020 Revenue Marketing Report, we found that the average marketer spends two to three days per month compiling reports. More than 36% of marketers still spend more than four days cobbling together data from CSVs, Excel, Google, CRMs, and marketing automation tools.
Add the time needed to compile data before analysis begins (up to five days per month). Organizations lacking automation spend nearly two weeks dedicated to analysis and prep every month.
No wonder Gartner found that only 54% of marketing decisions are influenced by data. What has us a little depressed is that only 23% of marketing leaders cite skill development as a top priority for their marketing analytics teams.
Do we have your attention yet? I sure hope so.
What Marketing Analysts Are Missing
There is a major disconnect between the skills and technology needed to uncover actionable insights and what leadership is willing to invest.
An analyst simply cannot cobble together marketing reports without a robust customer data platform that normalizes, deduplicates, and manages data hygiene. Without a data transformation layer, they spend half of their time trying to make sense of dirty data and match disparate data sources.
“Marketers must adjust tactics often, especially with the acceleration of development in digital marketing just since the beginning of 2020. The time for excuses is over. The data continuum connecting marketing and sales has never been more critical, and the lack of collaboration around this data is a chief reason CMOs move on.” — Peter Zaballos, Chief Marketing Officer
Put simply–each system looks at your buyers a different way, which makes getting them to talk to one another very difficult. Your business looks at buying entities as a combination of accounts and contacts. Your CRM looks at people as leads or contacts. Your marketing automation platform looks at people as email addresses (forget accounts). Your website looks at people as IP addresses. Your paid advertising can be a weird combination of things connected to your web activity using UTM parameters.
You want your marketing analyst to map your buyer journey, but it’s like asking them to investigate a person who uses multiple aliases depending on what part of the city they’re in. At their workplace, they identify themselves by only their social security number. They use a nickname at home, and at the grocery store, it’s their formal name. Without physical identification, it would be impossible to know these entities are the same person–which is precisely why your analyst struggles to piece together your buyer journey using CSV files and Excel spreadsheets.
If you have a platform that can connect your systems and make sense of them, your analyst can spend time uncovering patterns and anomalies. They can help translate what the data is saying into what can be done about it. This is why good analysts are worth their weight in gold. Sadly, they rarely have the capacity to provide these insights.
People have been advocating for data-driven marketing for a long time. More data than ever is available, and it’s possible to make sense of it. But to get to the place where we can truly say we’re data-driven–and allow your marketing analyst to make real contributions through insights–you must invest in a tool that can integrate your applications and make sense of them.
It’s time to walk the talk.
Considerations Before You Build or Buy
Marketing data is nuanced, and it helps to go with a product that offers a support organization that specializes in helping their customers adopt best practices. This means thinking through campaign hierarchies, schemas, and data transformation rules. For example, do you want a tool that will help merge duplicates in your CRM and marketing automation platform, or do you want to leave your employee-facing data as-is and try to maintain disparate systems? How would you handle nightly or hourly data refreshes in the case of the former?
Another consideration is whether you build the complex data models needed for attribution, account engagement scoring, and campaign effectiveness measurements or leverage models that have already been tried and tested.
Marketing tactics are always changing, which means the tools marketers use frequently change as well. Whether you’re building or buying a customer data platform, you’ll need to select an integration tool that’s flexible enough to keep up with your rate of change. This also means building new schemas and algorithms to unify your accounts and contacts across those systems.
To help you navigate these decisions, we’ve provided the 10 Pillars Every Marketing Analytics Tool Must Have and the six most common data gaps you’ll be solving for.
Please contact us if we can be of any help!