The Challenge: Cold Traffic From Meta Ads Struggled to Trust the Brand
The health and wellness brand in question was sending cold traffic directly from Meta ads to its product page.
The control was cluttered with gallery images that did not highlight nutritional facts and benefits, and generic copy that did not call out who the product served, and why it could solve specific problems better than alternatives on the market.
The traffic wasn’t pre-primed about the brand or the product either, and thus struggled to purchase with confidence.
Triangulation:
The hypothesis proposed and the changes made were not based on assumptions or a single quantitative data point. ConversionWise:
- Ran post-purchase surveys to understand what is important to customers buying products, such as the one we’re discussing, and the information they typically seek on the PDP. Here is what Kyle Foster, head of optimization at ConversionWise has to say about using post-purchase surveys well and turning them into your competitive advantage:
Use radio options/multiple choice questions to begin with – this increases opt-in rate.
Try to avoid kicking off with open-ended questions.
First, find out more about the buyer:
- How old are they?
- What is their gender?
- Is this their first time buying a product like this?
- What is most important to them when buying online (Reviews, shipping times, effectiveness etc)
Then, dive in further about the purchasing journey:
- Other than price, was there anything that almost stopped you from purchasing?
- What was the key motivating factor that made you purchase?
- What sounded most appealing to you about our product?
- What was going on in your life that made you click on our ad? (Pain points)
- What do you wish to solve?
I think where brands trip up is that they don’t have answers in mind before launching their surveys.
You should jot down information that you want to find out about the purchasing journey and then come up with questions based off of this.
- Reviewed scroll depth data for the product page. This flagged the fact that most buyers don’t read or reach sections with the information needed to build a compelling purchase narrative.
- Ran user tests to surface additional insights. And confirmed what the scroll depth numbers had indicated.
Final Hypothesis:
Based on data from post-purchase surveys and scroll maps, adding product benefits above the fold (beneath the description) and improving the initial image in the PDP image gallery will better educate cold traffic and new users on the benefits of the product. This will make them more informed and motivated to make a purchase, leading to an increase in transactions and revenue-per-visitor.
Test Design & Pre-Test Analysis:
The Control
The Variant
Variant. Improved Purchase Conversion Rate by 8.93%
Compared to the Control, the Variant:
- Added the total number of servings in one unit of the product to the first gallery image
- Took the USPs of the product – lost in the description – and pulled these up, with prominent icons, to the first gallery image
- Made for a sleek and easy-to-control gallery viewing experience with clear previews
- Gave context about the brand, why it is different, included a hat-tip to the buyer segment in focus (the “who”, in this case health-conscious women)
- Tied innovative product features to everyday benefits
Test Parameters & Testing Stack:
| Testing Parameter | Value |
| Number of Variants | 1 |
| Statistical Significance Threshold | 95% |
| Power Set | 80% |
| Traffic Split | 50/50 |
| Purchase Conversion Rate (Control) – Main KPI | 5.27% |
| Purchase Conversion Rate (Variant) – Main KPI | 5.74% |
| Uplift Percentage | 8.93% |
| Test Duration | 14 Days |
| Traffic Source | Paid |
Additionally, the following secondary metrics were also positively impacted:
Variant visitors and buyers:
- Saw 18% more pages after purchase
- 10% of them spent 20s or more on the website
- Triggered 6.6% more add-to-cart events
- Started a checkout process 7% more often
A full complement of aligned primary & secondary metrics – all positively impacted – is a nod to the depth of change initiated in customer behavior.
The variant implemented was building trust and capturing the attention of visitors better than the control, on all fronts.
Here’s how Convert Experiences helped:
| Feature | How | Learn More |
| GA4 Integration | It was used to set secondary KPI custom goals for easy tracking. | https://www.convert.com/integrations/ |
| Post Segmentation | Allows you to analyze experiment reports and results on the basis of segments like browser used, device used, new v/s old visitors and so on. | https://support.convert.com/hc/en-us/articles/360056333451-using-basic-and-advanced-post-segmentation |
| A/B Testing | Showing half the determined segment of site visitors the control, and the other half – the variant. | https://www.convert.com/features/ab-testing/ |
What Can You Learn From This Test?
- Triangulation is your secret sauce. Data doesn’t lie. But often biases can. If we want a particular problem to show up in our analysis, it likely will. Large & successful agencies like ConversionWise always rely on several data points (in different formats) saying the same thing to take action and frame a hypothesis.
- Properly researched changes positively impact the entire user/buyer journey. This was visible in the case study as multiple secondary KPIs – like pages visited after purchase, time on page, and checkouts started benefited from the adjusted PDP. A/B testing done well can even impact buyer perception and the tendency to re-purchase.
ConversionWise is a conversion design optimization agency focused on increasing conversion rates for their clients. Conversion design strategy, audits, techniques and implementation. Visit ConversionWise
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