Marketing Data: 5 mini case studies where marketers turned information into insight

This article was originally published in the MarketingSherpa email newsletter.

Finding opportunity in your marketing data often comes down to pattern recognition. Which one of these is not like the other? And why?

Here’s a simple example Flint McGlaughlin, CEO and Managing Director, MECLABS Institute shared in a coaching session about the Data Pattern Analysis (MECLABS is the parent organization of MarketingSherpa).

Do you notice the deviation in the pattern? The analytics platform calls it out in red, but here is a more obvious view.

What does that deviation from the pattern mean? And does it present an opportunity…or just a dead end?

Analyses and questions like these help marketers use their data to identify opportunities and drive results. To get you thinking of ways to find opportunities in your data, here are five mini case studies form your peers.

Mini Case Study #1: Looking beyond average customers led to 40% increase in website conversion for tourism company

“We examine our sales and marketing data constantly. But on occasion, there are some surprises so large that they make us rethink sacred cows in our business,” said Casey Halloran, Co-Founder & CEO, Costa Rican Vacations.

“I might be murdering this, but I think there's an old saying that ‘the problem with average data is that it's average.’ We found this out the hard way,” he said.

The company regularly examined customers’ average spend, average length of stay and average number of travelers. But one day the team decided to analyze the data in clusters and standard deviations. They found that the previous reliance on the average data was providing an inaccurate view of actual customer behavior.

“Our overuse of average wasn't telling us how dramatically different the outliers were from this average. In fact, there weren't that many real customers who looked like this ‘average client’ at all!” Halloran said.

This discovery inspired changes to the website’s search and product offering, catering to the outliers on the bell curve, versus previously grouping so much around what Halloran refers to as the “mythical average customer.” These website changes drove a 40% improvement in the site’s conversion rate.

For example, the slider for total budget was increased to a maximum of $20,000 in the site’s finder tool. 

Creative Sample #1: New homepage search

 

 “Sometimes you gotta slice the data differently and, ideally, by third parties who don't care about your old assumptions,” Halloran advised.

Mini Case Study #2: Segmenting CLTV helps technology research firm make smarter investments

Here’s another example of looking past average numbers and diving deeper into the data to get customer insights.

SoftwarePundit had calculated customer lifetime value (CLTV) to be around $200. This figure was calculated as an average of the entire customer base. Major inputs into the calculation were average order value (AOV), order frequency, gross margin, and churn.

“While digging into our churn data, we realized that we had a material percentage of one-time purchasers, and if a customer purchased a few times in the first few months, they basically never churned. Given that churn is a major input, we decided to segment and recalculate our CLTV,” said Bruce Hogan, CEO, SoftwarePundit.

The team discovered it had a material percentage of its customer base with a CLTV around $20 and a material percentage with a CLTV closer to $1,000.

“This insight had two significant impacts on our marketing,” Hogan said. First, it increased the amount of money they were able to spend acquiring customers, provided the team could determine the customers weren't one-time purchasers.

Second, they ran a series of lifecycle marketing experiments focused on getting one-time purchasers to repeat purchase at the early stages of their lifecycles. Through A/B testing, they found a few tactics that nudged shoppers to repeat purchase, and for a small fraction, this turned into a habit that increased CLTV.

For example, they sent emails with coupons offering a 10 to 20% discount on subsequent purchases. Of the tactics they tested, the coupons resulted in the biggest absolute increase in repeat shoppers. However, most shoppers who used the coupons did not become habitual buyers after the coupons were no longer sent.

Another effective tactic was product recommendations. The company’s data science team identified the products that were most often purchased in customers’ second and third orders. When first-time buyers returned to the site, they would get advertisements for these products, in addition to email promotions and social media targeting. This tactic had a higher ROI than the coupons but did not have as large of an overall impact.

“It's critical to segment CLTV. You're better off having an accurate average CLTV than not having a trustworthy figure. However, there's a good chance that this figure doesn't actually describe the CLTV of any individual segment in an accurate way. By segmenting your CLTV, you can unlock more dollars for acquisition marketing, and uncover experiments that will increase CLTV,” Hogan said.

Mini Case Study #3: Targeted SEO outreach helps reviews website garner 178 quality links in two months

Trond Nyland, Founder & CEO, Mattress Review set out to build strong SEO for his website by getting lots of links from quality websites using traditional SEO techniques like guest posting and blogger outreach.

Nyland took a data-driven approach to target this outreach. “We used Ahrefs to get data on which high-quality websites give out lots of backlinks. We figured these websites would be most likely to link to us and specifically focused on targeting them,” Nyland said.

His team focused 80% of its effort on these high-potential websites. After two months, they'd gotten about 170 links from the high-potential websites and just eight from all the other websites. That represents a more than 400% improvement in efficiency by targeting websites that, statistically, give out lots of links. “Long live data!” Nyland said.

The team was able to garner a Domain Rating of 51 in about four to five months using this targeted approach.

Mini Case Study #4: A/B testing helps increase Facebook ROI for auto detailing website

Question everything.

And then let the data show you the way.

“We have discovered that when running Facebook advertising campaigns it is more effective – in ROI terms – to duplicate the campaign and deploy additional capital rather than increasing ad spend on the existing campaign,” said James Ford, co-founder, AutoBead.

The car detailing website ran A/B tests across nine recent campaigns to validate this insight. The approach resulted in a 21% increase in revenue for the duplicated campaigns versus increasing the spend on existing ads.

Mini Case Study #5: Heatmapping helps nonprofit decrease homepage exit rate 3.5%

“While marketing data traditionally helps organizations increase their sales or visibility, in the nonprofit sector, marketing data is crucial to support direct services,” said Susan Ruel, Director of Marketing, Momentous Institute.

The social emotional health nonprofit offers a variety of services including a school, therapy and professional training. At the beginning of 2019, the Momentous Institute team noticed homepage click-through rates were decreasing as exit rates increased. “While I believe the data derived from the basic Google Analytics helps alert marketers to an issue, additional data is often needed to properly diagnose the issue and develop a logical solution,” Ruel said.

So the team used website heatmapping to try to better understand visitor behavior. The heatmapping data showed that homepage visitors were clicking the logo as if they believed they weren’t on the homepage and that the search icon on the left-hand side of the navigation was one of the most clicked-on buttons.

Creative Sample #2: Confetti heatmap of nonprofit’s website navigation

Based on the heatmapping data, the team determined that visitors were overwhelmed with the 13 click options and were not being served click options they expected to receive from the homepage.

The marketing team redesigned the homepage, creating a cleaner main navigation that narrowed down click options to eight and included links to all of the nonprofit’s services.

Creative Sample #3: Nonprofit website’s nav before redesign

Creative Sample #4: Nonprofit website’s nav after redesign

Once the redesign was launched, the homepage exit rate decreased by 3.5% and the amount of time visitors spent on the homepage decreased by 4.8%. “While traditionally the goal is to keep visitors for an extended time, I consider this decrease a victory as it shows visitors could find their desired information quicker,” Ruel said.

But most importantly, click-through traffic from the homepage to Momentous Institute’s direct services – Momentous School, therapeutic services and trainings – increased. “As a nonprofit marketer, it is incredibly rewarding utilizing marketing data to bring additional exposure to your organization’s direct services,” she said.

Related Resources

Data Pattern Analysis: Learn from a coaching session with Flint McGlaughlin

Data-Driven Marketing: 7 examples of using data as a force for the good

Get Your Free Simplified MECLABS Institute Data Pattern Analysis Tool to Discover Opportunities to Increase Conversion

What is Data? A discussion about getting value from your marketing analytics