How to make Analytics the cornerstone of your marketing

Guest Column: Tiffany Delmore, the co-founder of, writes that the interplay between metrics is what matters the most, and is what’s most difficult to teach

e4m by Tiffany Delmore
Updated: Oct 26, 2020 9:52 AM
tiffany delmore

Never have analytics mattered more. Marketers know that, but more than three-quarters of them admit their analytics skills are lacking.

According to Marketo’s “Definitive Guide to Marketing Metrics and Analytics,” 77% of B2B marketers say ineffectively using data and analytics is one of their team’s top five weaknesses. At the heart of the issue is that they tend to look at channel-specific data, not their overall marketing effectiveness.

Marketers who put the puzzle pieces together contribute more to the company’s bottom line. How well a social media post ranks isn’t important; how social media plays into the larger strategy, such as funnelling users to the company’s site, is.

By analyzing not just campaigns and channels, but whole systems, companies can make analytics the cornerstone of their marketing.

Thinking in sets

According to MarTech Advisor’s Indrajeet Deshpande, marketers share six common data sets: web analytics, visual behaviour and testing, search engine optimization, social media performance, content analysis, and email effectiveness.

Let’s take each in turn:

  1. Web analytics

Web analytics measure information like the number of visitors a site receives, how many times a page is viewed, what domains tend to refer visitors, what actions visitors take, and how often visitors bounce.

Data like these are only a fraction of what analytics programs can provide. Some, like Calendar, can correlate online data like calendar events with real-world behaviour. An account-based marketer might ask about a CMO’s meeting habits to understand his online activities, such as visits to vendors’ sites.

Again, it’s about thinking in systems: Marketers must be able to draw lines between different sites, real-world activities, and purchasing behaviours.

  1. Visual behaviour and testing

Visual behaviour and testing connect the dots between quantitative actions and actual usage. For example, a heatmap can identify common clickstreams. Direct observation can help marketers put together case studies. Case studies can help marketers empathize with users in ways that raw data simply can’t.

The other component of this category is testing. Processes like A/B testing help marketers decide whether a campaign or component is not only a solution but the best solution. Experimentation can uncover optimization opportunities that aren’t apparent in raw data.

  1. Search engine optimization

A third set of data has to do with SEO. Search engines use dynamic algorithms to help searchers find the most relevant, valuable results to queries.

Why does SEO data matter to marketers? Because the higher in search engine results pages a company ranks for a relevant keyword, the greater the traffic it gets.

SEO data should be reviewed in conjunction with web traffic. For example, if a page isn’t getting a lot of visitors, marketers should check its most common referring keywords. Visitors may not be searching terms that the page appears for.

  1. Social media performance

Social media campaigns can increase customer engagement, grow audiences, and drive traffic to company websites. As with SEO, social media data should be reviewed alongside web analytics and findings from user testing.

A good example is reach. Growing your reach on social media is also likely to boost your web traffic. And because search engines take social media sharing into account, it might also boost your search ranking for related keywords.

Social media analysis allows marketers to see how effective and ineffective campaigns compare. The analysis also helps provide information on ROI which shows the value marketing adds to the bottom line.

  1. Content analysis

Content analysis touches SEO, social media, visual, and web analytics. Content that performs well on social media will perform better in search. Chances are, it’ll also drive more traffic to linked websites.

One cross-category content metric that matters is click-through rate: How frequently do content impressions actually translate to website clicks? Testing can increase CTR by, for example, comparing how a link performs when placed high in the article to in the last sentence.

The Covid-19 crisis makes the content analysis even more important. Home-bound get more of their media and make more purchases online than those who go out frequently.

  1. Email effectiveness

Email is still a critical tool for reaching out to an audience. However, indiscriminate email campaigns often result in messages being sent directly to junk and spam folders.

Email analytics ties closely to content and web analytics. For example, an email campaign with a high bounce rate may indicate poor-quality content. One with a poor clickthrough rate may not do much to increase website visitors.

One underappreciated email metric is the unsubscribe rate. If readers unsubscribe frequently, it could indicate an audience misunderstanding. Understanding what metrics mean for the wider marketing strategy is the essence of data-driven marketing.

While some companies care more about certain metrics than others, the bottom line is the same: Making analytics the cornerstone of your marketing isn’t about any one metric. The interplay between metrics is what matters most, and is what’s most difficult to teach. Tools can help, but for that, there’s no substitute for training and experience.

Disclaimer: The views expressed here are solely those of the author and do not in any way represent the views of

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