In the days before digital marketing, it was difficult for marketers to correlate specific marketing efforts with specific revenue outcomes. Marketing was more of a “spray and pray” proposition than it is today.
In a data driven marketing world, there are a variety of tools available to marketers that can help them to understand the paths to revenue that are working best.
Ultimately, a data driven marketer should be able understand which of the flows through the marketing and sales funnel are resulting in the most revenue.
The path to revenue flows through KPIs such as pageviews, visitor clicks, visitor conversions and salesperson lead disposition. So, while a data driven marketer should never hang their hat on, for example, conversions alone, data about conversions can be used as part of an understanding of the complete funnel progression.
If it’s determined that most company revenue flows through specific content and specific conversion points, a marketer can then ask him or herself, “what can be done to drive more visitors to that content and get more visitors to convert at those points?”
The ultimate for a data driven marketer is knowing that $62,309 in revenue last month resulted from people who found blog post A, clicked on CTA B, and filled form C. But there are some dependencies for getting this data.
The Salesperson Contribution to Data Driven Marketing Efforts
In order for marketers to have accurate bottom of funnel KPI data, it’s important that salespeople are bought into and regularly contribute to their part of the tracking process.
If salespeople do not regularly indicate the disposition of leads within a CRM system or if they don’t ensure that opportunities have the right lead source or if they don’t close out won opportunities with the correct revenue amount, the result will be “garbage in, garbage out”.
Aggregating Marketing Metrics
Since marketing data can come from a variety of sources, it’s best if that data can be automatically aggregated in order to minimize manual aggregation effort.
Dashboard tools such as Tableau and Klipfolio are good options. Google Sheets can also be used as a free and effective data aggregation platform, with the help of add-ons for connecting to Google Analytics and to a CRM system.
Goals as a Data Point
Regardless what dashboard tool is being used, goals should be included in the charts. It’s always good to have a visual bar against which to measure progress.
KPIs for Data Driven Marketers
Here are some of the data points at different stages of the sales and marketing funnel as well as some tools that can measure progress.
SEMrush provides a marketer with just about all the data they could ask for about keywords, competitor keywords, backlinks, site health issues and more. Our advice is run, don’t walk to SEMrush.
This may seem like an obvious KPI, but analyzing pageviews using Google Analytics is often done on a macro level, but not a micro level.
In other words, if 80% of our organic traffic comes from 20% of our blog posts, maybe we should zero in on the performance of the top posts and analyze what actions visitors take.
Embedded Video Views
While views of an embedded YouTube video can be tracked in Google Analytics, it’s easier for a marketer to track video views using a tool such as Wistia. In fact, Wistia automatically writes to Google Analytics events.
Ungated Content Clicks
Every piece of downloadable content should have Google Analytics event tracking code associated with it. Then, the interest level in specific pieces of downloadable content can be measured.
Calls to Action
By adding Google Analytics event tracking code to all of a website’s CTAs, marketers can see which CTAs are resulting in the most clicks. We recently discovered that our most clicked CTA was a sentence of inline text on a blog post — not one of our end of post banner CTAs.
Inbound Phone Call Traffic
By presenting different phone numbers on different pages with an application such as CallRail, marketers can easily see which pages generate the most inbound call traffic.
The message on CallRail’s home page is “Call Tracking For Data-Driven Marketers”. Among CallRail’s many capabilities is the ability report call volume into Google Analytics inbound on a per page or per campaign basis.
Landing Page Conversions
Marketing automation systems and landing page point solutions such as Leadpages and Unbounce provide data on unique visits and conversions. Most of these also support A/B testing.
It’s almost impossible for a person to accurately predict which variant of a landing page will produce a higher conversion rate. With A/B testing, visitors vote with their clicks and taps. Marketers can set up their own A/B tests without the need to get IT resources involved.
Split Test An Entire Website
As an email testing company, Litmus is really good at testing. In the case of their website, I was variously greeted with different color schemes and different messaging depending on when I visited their site over a several week period.
Litmus appears to have talented web developers who code the variants in the Bootstrap framework — so this is a level of testing that’s not easily available to everyone.
CRM Lead Disposition
This is a data point that’s dependent on salespeople either converting qualified leads or disqualifying leads that don’t have potential. The reason a lead was disqualified can be an important data point for marketers.
Salespeople should not only create opportunities by converting qualified leads — they should also create opportunities that resulted from inbound phone calls. The source of the Opportunity should be set to “Phone Call” so that marketers can measure the effectiveness of that inbound channel.
With an application such as CallRail, it’s possible to attribute a source to a specific website page. If that information is manually or automatically correlated to the opportunity, that’s an additional good data point for a marketer.
The final leg in the buyer and data journey is won opportunities and their revenue amount. This is also an element that requires diligence on the part of salespeople. The value of the opportunity should be changed to the actual value from what may have been an estimated value during the sales process.
A high level of buy-in and cooperation on the part of salespeople allows for directly correlating PPC campaigns costs with revenue. This is one of the most actionable data points for a data driven marketer. If we know that a $10 PPC campaign expenditure resulted in $100 in revenue, then we should spend more on that PPC campaign.