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11 months ago
 

Using analytics to identify (and stop) falling conversions

Every travel company wants to use data to make the right decisions about marketing, but the reality is that it’s still a challenge to wade through loads of metrics to find insights that really mean something.

NB: This is a viewpoint by Tony Gray, senior director of North American Professional Services for Webtrends.

Digital analytics data can help marketers make wise decisions – and it can also be an important source for ‘uh oh’ alert when a problem arises, such as a conversion drop.

Let’s walk through four steps that illustrate an example of data-driven decision-making by a large travel brand, where an analyst spotted a significant drop in conversions using analytics, investigated it, identified the cause of the underperformance and then – most importantly – did something about it.

Step 1:
Understand demand, conversion and other key measures (bounce rate and error rate, for instance) by top markets

This travel business had already identified its  most important originating markets. Originating markets are defined as the departure city/area for the activity.

This view is important as it often leads to different profiling and segmentation opportunities based on that geography for marketing programs.

At a regular channel performance meeting, a group of employees reviewed the following:

SC JAN WEBTRENDS step1 table

Market Level Demand, Transaction & Key Metrics for Top Markets

(Click on the table for a link to a larger version)

At first glance, it’s clear there’s been a year-over-year decrease in demand (the ‘Visits with Purchase Funnel Interaction’ column) across all markets. But one that stood out was the alarming decrease in conversions for Las Vegas.

With visits up more than 16 percent, a drop in conversions of more than 18 percent appeared incongruent. While there are other data points worthy of investigation from this table (Why is the error rate for Atlantic City so high? And what’s the driver for Orlando’s stellar conversion rate?), for this example we will dig deeper into Las Vegas.

Step 2
For any markets with a significant level of conversion decrease, begin exploring at the traffic source level.

Looking at channel performance is a great way to start. This particular travel brand was spending loads of money on paid search and other digital advertising channels to drive visitors to Vegas site content and Vegas-themed landing pages. So traffic going up for Vegas made sense – but the conversion rate decrease was concerning. It was time to look closer at traffic source data.

SC JAN WEBTRENDS step2 table

Las Vegas Demand, Transactions & Key Metrics by Traffic Source

(Click on the table for a link to a larger version)

Here we see immediately that conversions are down across all traffic sources for Vegas. However, an anomaly appears in that paid search is driving a significantly higher year-over-year increase in traffic – almost 44 percent more – but with a substantial decrease in interactions with the purchase process and large year-over-year increases in bounce and error rates. So why the decrease in conversions for this important demand channel?

Step 3
Review poor performing channels at the campaign level for significant changes in key measures

Time to dig in to the specific campaigns within the paid search traffic channel.

SC JAN WEBTRENDS step3 table

(Click on the table for a link to a larger version)

With so much money being spent on paid search, the company was on high alert for performance and the commensurate return on marketing investment.

Looking at the data for all campaigns within paid search, it appears there are two with severely lagging performance when it comes to conversions: Google Brand (a 27 percent decrease) and Kayak-Resort (a 37 percent decrease). That leads us to the most important and actionable step.

Step 4
Analyze campaign(s) for understanding of decreases in effectiveness (i.e. spend levels, creative, placement, landing page, quality of traffic, etc.)

With data in hand, it was time to work with the channel owner and marketing campaign managers to determine what had changed to result in such deteriorated performance.

After some research, a broken link was discovered in one of the Kayak-placed ads. Easily fixed and campaign performance bounced right back.

For the Google ad, marketers determined that the search results ad copy did not correspond with the content on the landing page it drove people to. In other words, visitors expected to see one thing and got another – and that meant they bounced off the page. Several different versions of a more relevant landing page were created and tested through a series of A/B and multivariate tests, and again, conversions were back on track.

The results: avoiding the fire drill

These types of lows (and highs) in marketing performance happen frequently. And too often, it creates a melee of people running around looking for immediate answers and action. By consistently monitoring the data that matters, having a solid process for action and strong capabilities to support the on-the-fly data exploration needed (such as Webtrends Explore provides), you can avoid the fire drill and rapidly fix any issues in your marketing campaigns.

Oh, and one of the best reasons to follow these four steps is that you’ll stay ahead of the game – you’ll know what’s happening (and have a solution) well before your CMO or CEO comes knocking on your door!

SC DEC webtrends logo 350w

NB:  This is a viewpoint by Tony Gray, senior director of North American Professional Services for Webtrends. It appears here as part of Tnooz’s sponsored content initiative.

NB2: Image by Shutterstock.

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About the Writer :: Sponsored Content

This is the byline under which Tnooz publishes articles that are part of our sponsored content initiative.

 

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  1. Sam Fulton

    Great walkthrough! This brings back so many memories of how data like this was used at Orbitz when you were leading the BI team. Keep up the good work and stay in touch as I am sure Orbitz misses you!

     
 
 

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