“We don’t have enough data.”

This is a common refrain from brands as they begin to ‘go digital’ and launch more campaigns, but hesitate to deploy comprehensive analytics.

Or it’s the line used to ward off assertions that advanced analytics could be the key to successful omnichannel marketing.

The thing is: there is always enough data to improve marketing performance

Allow me to explain. There are many ways to improve marketing’s ability to accomplish its objectives.

Each of these analytical methods is at its best with first-party (internal) data, like the juicy stuff found in campaign measurement, but each can also benefit heavily from the application of third-party (external) data.

Even without consistent campaign data, however, there is always a wealth of insight to be garnered from analyzing first-party data, both digital and otherwise.

Data-driven decision-making was the most critical method for driving growth for 83% of enterprise marketing executives in 2015, according to an Association of National Advertisers study.

Each of the following types of data are almost certainly somewhere in your organization.

The trick is, of course, extracting them at a speed that enables marketing rather than hinders it. But that’s less difficult that one might think these days.

Once extracted, the data must be “harmonized” (taught how to play nicely with other data) in order to enable cross-channel, cross-regional and cross-departmental insights.

We call this “quantitative marketing” – the idea that marketing can be as much science as it is art. 

Sales (or Conversions or Transactions or Orders)

If you don’t have this data, you’re not in business. Okay, okay – you, marketing executive, may not have this data, especially not in any way that is valuable to your marketing decision-making.

But some silo somewhere in your organization holds this treasured data set. And it can inform marketing a great deal.

Obligatory stock photo of some silos

The more “digital” your business category, the more likely it is that this data is easy to access.

For example, ecommerce tends to lend itself quite readily to the spread of sales data, since it is inherently collected in digital databases. But brick-and-mortar categories are a few degrees more complex.

Even more complex are CPG and some B2B2C businesses, whose sales data is consumed outside of their organizations and (hopefully) reported back accurately and with ready utility. 

So, how to use sales and conversion data to improve marketing:

  • Analyze the data itself. Do certain products sell more than others? Have you run any campaigns for those products, or are the products you’re marketing not selling well?
  • Overlay the sales or conversion data onto your trendlines for spend and KPI breakdowns for different segments (territories, channels, tools, agencies, etc.). “Correlation does not imply causation” is relevant here – but that doesn’t mean correlations aren’t sometimes meaningful.
  • Contract (or better yet, hire) a data scientist to run cluster analyses (and other fancy names of fancy mathematical techniques) on the data. Performance by geography, product category, product color and other attributes inform a variety of business operations. Marketing can use the insights to grease the engines of campaigns.

Spend

It feels counterintuitive to reference marketing expenses as an opportunity for improving marketing performance, but hear me out.

There are three primary types of marketing spend data:

  1. Media buys.
  2. Agency vendors.
  3. Marketing technology vendors.

Typically, agency vendors includes some media buy and some marketing technology, but it’s difficult to truly parse the percentage of each with many vendors.

Some vendors combine two or three of these spends into one bundled cost, like conversion shops you pay a cost-per-lead fee, or aggregators, or programmatic media. 

It seems a lot of the marketing world gets caught up in the parsing of these costs, when what really matters is that all costs must be accounted for.

Media-mix modeling/optimization is one way of analyzing the spend (media buy) vs. the return (sales) using statistics.

But the same theoretical models can be applied to martech and agency vendors – using data science to predict which vendors will deliver what results.

Even if you don’t go that deep, however, a lot can be gained from the quantification of spend data, and the visualization of spend alongside sales, with all available breakdowns.

Third-party data

Ingesting and analyzing third-party data gives quick wins to large marketing organizations. Here are some examples:

1. Ever wondered if your offline campaigns are connecting with the right audience? ComScore just acquired Rentrak – and the two together provide fascinating levels of detail into offline audiences.

2. Ever thought about what’s working and what’s not working on your website? Google Analytics is free. Use it – and hire someone who knows how to dig up truly meaningful insights.

3. Ever wondered if your campaigns are successful driving awareness? If you’re consumer-focused, use social listening technology to analyze what people say about your category vs. your competitors vs. your brand/product.

4. Looking to see how well you know your target audience, online opportunity and customers? 

Dig into Facebook Audience Insights (for free in its advertising portal), run your emails through TowerData, analyze deep mobile demographics/psychographics with PushSpring or Analyze Corp’s Clientell tool.

5. Considering launching paid search campaigns? Use tools like SEMRush to approximate competitor investment in paid search.

6. Considering launching a new social presence or new social accounts? Use owned social analytics tools, coupled with social listening technology, to derive what your competitors are doing, and which of their activity seems successful.

7. Considering launching display advertising campaigns? Use Moat.com to analyze how your competitors are using online display.

The list keeps going…

…and this is just the tip of the iceberg of the applications of data to marketing activity – but you get the two big ideas:

  • Useful data is out there.
  • Useful data is in your organization.

These types of quantitative analyses are foundational to marketing success. As Mike Schmoker said…

What gets measured (and clearly defined) gets done.