Helping to grow Iowa businesses using a metrics approach to marketing

How Big Tree Marketing is Growing Iowa-Based Businesses

We believe you don’t have to be based in Silicon Valley to have a highly successful online business.  In fact, many of our clients have found that basing their business in the Midwest comes with distinct advantages, the most common being the low cost of getting setup.

Big Tree Marketing is helping local Iowa businesses compete online with a unique metrics-based approach to online marketing.  We combine Conversion Rate Optimization with Search Engine Marketing and Targeted Ad Placement. Throughout the process we monitor performance and make adjustments to insure the maximum ROI.





“Our online business has grown over five-fold in the past few years, and our marketing partnership with Big Tree has been instrumental in that success. Their expertise, professionalism and strong bottom-line driven approach have yielded tremendous results, from our PPC campaigns to SEO to site conversion rate optimization.”

Gabriel Openshaw Vice President, E-Commerce Overland




Why Iowa?

Iowa is our home.  The people, sense of community, and strong work ethic more than make up for the lousy weather.  While we do have clients outside of Iowa, even some projects that take us abroad, our preference is to support local businesses whenever possible.

What “local” clients have you worked with?





Reason # 9001 to be very careful A/B testing – Bot Traffic

Reason # 9001 to be very careful A/B testing – Bot Traffic


Robot spider

An e-commerce client requested a higher converting version of their product page. Their sales cycle is very seasonal (remember this, it’s important later) so time was of the essence.

We took a data driven approach to improve conversion rates and came up with a series of recommendations based on:

  • Analytics data
  • User replay sessions
  • Heat maps
  • User surveys

Our client spent the time and money to quickly code the new product page and place it on the site as the default version with the option to redirect users to the previous product page.


Testing Time:

We setup a split test in Visual Website Optimizer and waited for results.


Our first version broke even:


 So we made some more improvements based on further analysis and started another test.


Our newest version was getting crushed.



We made some small tweaks to what seemed to be a breakeven page and now our new page was both converting significantly worse and while still early in the test, losing significantly. We knew traffic was slowing down and conversion rates would decrease as we got out of season, but this was completed unexpected.

This didn’t make sense.


We started going through the list of possible reasons.

  • Confirmed numbers in analytics
  • Checked across segments
  • Device specific analysis.


All the numbers lined up, we were getting killed.


Enter Bot Traffic:


Bot traffic is a growing pain in the butt in modern analytics. Bad bot traffic is growing every year and they are getting smart. Changing user agents, IP addresses, reading javascript (this pinging your analytics), and other tricks to make them harder to detect.


Our friends at Distil Networks estimate that in 2015 only about 54% of web traffic were human visitors.


The remaining site visits are broken down into two categories:


Good Bots and Bad Bots


Good bots are your friends. They include search engine crawlers and performance monitoring software.


Bad bots are unique from many other security threat types in that their manifestations can be as varied as the businesses they target. Bots enable high-speed abuse, misuse, and attacks on websites and APIs. They enable attackers, unsavory competitors, and fraudsters to perform a wide array of malicious activities including:

  • Web Scraping
  • Competitive data mining
  • Personal and financial data harvesting
  • Brute force login and man-in-the-middle attacks
  • Digital ad fraud
  • Spam
  • Transaction fraud


Often through no fault of your own your website gets hit by some of these bots. In most cases, your website is not the target but your analytics data suffers.


However, we did our research and were already excluding bad bot traffic.

bad bot traffic in Google Analytics



Good Bots – the culprit skewing our tests:


This website had a performance monitoring service check their product pages about thirty times per hour to verify add to cart was working correctly. These visitors came from different IP addresses and seemed like real users. However, they never left the product page.

How our test was ruined: 

More importantly, our good bot friends were never redirected to the Old Product Page BUT were counted as visitors for our New Product Page (the control in this test because of how their development team implemented this test). We’ve reported this to Visual Website Optimizer as an issue.


In response, our split test sent more of the traffic it could redirect to the Old Product Page. This was real traffic that could convert. After review we discovered that our Good Bot performance monitor was accounting for about 400 visits per day to New Product Page, 0 visits to our Old Product Page, and 0 conversions. As traffic decreased due to seasonality, this had a larger impact on our second test and skewed the results from break even to losing significantly.


Finding More Conversions:

We used VWO’s custom visitor targeting to exclude the Performance Monitor bot and re-ran the test.


a-b testing improved results


Reminder for your tests:


Treat your winners like losers and double confirm your numbers. In this case our “control” was the new product page and we had good reason to believe it was going to win. The fact that it lost significantly forced us to double check for testing issues.


However, imagine this was reversed and your new page absolutely crushed the old page because you had a flaw in your testing method. Odds are you are less likely to question those results because you want your new page to win.


Always check for issues such as:


  • Bot traffic that impacts only one variant
  • Redirect issues for split tests that alert your viewers something is up


Case Study: Overland Sheepskin


Overland is a luxury brand which has already put a large focus on improving their website. Our challenge was to find new areas of hidden value to generate additional sales, but without compromising the existing SEO strategy.

We started with an Analytics Audit and Customer Journey Mapping.  The first step in improving Conversion Rates is to understand current performance and the customer journey.  Our data highlighted several opportunities to improve navigation, product page layouts, and shopping cart checkout experience.  After A/B testing, before committing to new pages or navigation, we then did a full SEO analysis using an SEO platform called Conductor, to insure that changes would not disrupt SEO performance.

The following results are still preliminary. As we continue to refine and improve the customer experience we expect conversion rate improvement to continue to grow.

Cart: Improving button location, reinforcing guarantee & free shipping, as well as cleaning up product presentation yielded a 23% improvement to checkout conversion.

Removing confusing fields increased conversion by 11%

Migrating to a more intuitive search and filter service increased conversion, while actually growing S.E.O. driven revenue.

Improve Your Conversion Tracking

3 things your business is missing in accurately attributing conversions

Your business is exclusively using Google Analytics to track conversions.
Google Analytics is an amazing analytics platform… but wether by intention or not, it does a better job attributing conversions from Google (adwords and organic), than it does other outside vendors.  If you are running Facebook, Twitter, Bing AdCenter, AdRoll, Pinterest, etc. you should consider installing conversion tracking for each major channel.  I’ve experienced that Facebook ads perform many times better than Google Analytics gives it credit for — but you’ll only be able to verify this with the proper tracking setup.

Concerned about slowing down your site with all the extra conversion tracking code?  Try switching to Google Tag Manager.



Your business is blindly attributing view through conversions.

First, what is a view through conversion or VTC?  A view through conversion, unlike a Click Through Conversion (CTC), is a soft conversion that attempts to attribute conversion value simply based on someone viewing your ad (but not clicking on anything).  The assumption is that just the view of your ad played some part in reminding your customer about your product, and that even though they didn’t click on your ad, it did influence their buying decision.  This is a fair assumption, but the danger comes when you just blindly accept all view through conversion as part of your value stream.  View Through Conversions need to be attributed according the the value they provide.  In the case of an “infomercial” type video on Facebook, a view through conversion with an attribution window of 24 hours, likely holds some real value.  But my experience is that AdRoll and other companies have been exploiting view through conversions by cramming inexpensive banners across millions of sites on their extensive content network.  The result is that just about ALL your customers will have been exposed to the banners at some point, and so they try to take credit for all your sales as view through conversions.The point is, when attributing value to a campaign, dig deeper and look into what you are attributing and why.



Your business is forgetting to consider multi-touch conversions.

The larger the purchase, the longer the buying decision.  A user might discover your product via a Google Ad, request more information as a result of a re-marketing Facebook campaign, and then make a final purchase based on an email promotion.  How is your business attributing value to each one of the campaigns?  If you have Google Analytics on auto-pilot, where it chooses, then you are likely not seeing the full picture.A highly recommend the Google Attribution Modeling Tool.  You can easily check different attribution models for your various campaigns.  Compare last touch modeling to first touch modeling, how do the conversions shift among your different campaigns?  You can also look at last non-direct click, or time decay, or even create your own custom model based on your customer journey mapping.

Case Study: MarathonFoto

Case Study: MarathonFoto



Challenge: MarathonFoto has been watching email response rates decline over the past 3 years. This was a result of list fatigue, but also new promotional mail filters implemented by GMAIL. Our marketing team was tasked with finding alternative marketing channels to reach race participants with photo purchase offers.


Journey:  We first experimented with Google Adwords and Search Engine Optimization, to target people searching for race photos.  While this campaign was very successful from an ROI standpoint, and is still running today, the audience is capped to people explicitly searching for the photos and visitors are still required to search for their photos once they land on the site.


Solution: Our team developed a custom facebook marketing solution using cookies, and collaboration with race websites, to market personal thumbnail images on Facebook directly to race participants.  What does this mean?  Well, lets say you ran the ‘Run Till You Drop’ 2015 Marathon.  72 hours later you are on Facebook and you see a thumbnail picture of you, right in your newsfeed courtesy of MarathonFoto, with a direct link to your my photos page on MarathonFoto.  How is this possible?  That’s our trade secret.  But the results were a game changer for the business.

Response rates were off the map.  Our ads were receiving CTR of 40% and higher for major events.  Our ROI, using only Click Conversions (zero attribution for View Through Conversion) was between 10:1 and 20:1 depending on the event.  In addition, the free thumbnails were a win for the races, because they built a lot of positive buzz about the event on Facebook.  Our tracking showed a very high percentage of postive re-posting, commenting, and liking, leading to organic impressions and brand building for both the events and for MarathonFoto.