Suggestions for Historical Data Comparison

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Suggested reading: Historical Data Comparison on Onsite Analytics

Historical Data Comparison on Onsite Analytics helps you compare key metrics for your campaign results over two different date ranges. This allows you to gain valuable insights into changes in key metrics and the performance of your campaigns over time. You can leverage this feature to better understand the impact and growth of your onsite campaigns, making it easier to make data-driven decisions and optimize your marketing strategies accordingly.

This guide aims to explain how to approach the data comparison results and offer suggestions on how to improve them.

Understand results

Conducting historical data comparisons on the key metrics and analyzing the right metrics will result in insights and trends and pinpoint the campaigns that can be improved.

Two critical metrics are indicators for improvement areas: Incremental Revenue & Conversion Rate (CR) Uplift. You can check for any increase or decrease in these two metrics to understand where to improve performance.

The diagram below displays this general approach on these two metrics.

To obtain actionable insights, you can follow these best practices to analyze the results: 

List campaign variations looking at conversion rate uplift from low to high

  • This practice helps you identify variations with negative CR Uplift. These are the campaigns that you have to review and take action on to improve performance. You may also end the campaign if the significance is high and you have concluded that the variation is ineffective in reaching conversion goals.
  • You can also identify variations that have high CR Uplift. You need to compare low-performing scenarios with these campaigns and take them as reference points to determine what can be changed in segmentation/rules and design.

Filter variations that have significance value over 85%

Taking action when the campaign reaches a significant level is essential. Significance is a statistical term used in A/B Testing that indicates whether the data is sufficient to continue or end the experiment. This score determines the significance of the results and guides decision-making.

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Suppose the analytics lack significant results, as most campaigns have a low significance level. In that case, you can review the segment and campaign rules to ensure the campaign is accessible to a larger population. Expanding the audience will decrease the period for collecting the data required to reach a valid significance level.

Exclude/filter campaign variations with low impression

Similar to significance level, campaign variations with very low impressions can be misleading while assessing results and planning the next steps. You can exclude variants with a low sample size and conduct the analysis on a more data-driven and significant basis. 

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The Onsite Analytics page has a default filter to display the variant results with impressions higher than 200.

Instead of excluding variants one by one, you can set a minimum impression threshold to list the relevant variants. 

Enable data comparison

It is strongly recommended that the compared ranges be equal in duration for an accurate and reliable comparison and a balanced number of campaigns to compare. For example, you should avoid comparing 10 days to 30 days. Even in cases where the compared ranges are equal (i.e., 30 days to 30 days), the sample data will not be balanced if the number of campaigns compared is 5 to 25. Therefore, the comparison result will not be healthy to drive accurate insights.

Improve results

It is strongly recommended that you duplicate your campaign before making any changes to its traffic allocation, goals, segments, or rules. This helps prevent any discrepancies in the analytics and ensures accurate tracking of campaign performance.

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The recommended actions are not exclusively for the specified metrics. The actions suggested for a particular metric can also be applicable to increase others. For example, possible actions for incremental revenue can also help increase incremental conversions as they are related.

See below for possible actions and recommendations for metric comparison results:

Decrease in Conversion Rate (CR) Uplift

Possible Actions/RecommendationsExplanation
Increase the traffic allocation for winner variants on your significant A/B test campaignsIf the significance level exceeds 95%, you can list your variations based on their conversion rate in descending order, and increase the traffic allocation of the winner campaigns. This approach will help identify the most effective variants for further optimization.
Increase the traffic allocation for winner variants on your campaigns with high probability to win

List your variants based on their conversion rate in descending order, and increase the traffic allocation of the winner campaigns.

Set the priority between campaigns

Priority enables multiple campaigns that can be displayed on the same page to be displayed in a priority order. For example, if you have 10 campaigns and you want 3 of them to be in a priority order, you need to add priority to all your active campaigns. You can prioritize the campaigns that are performing better and driving high revenue.

Work on the campaign design considering UX/UIEffective campaigns are the ones that build an appeal for the audience. You can review the design decisions and make changes in the UX. You can take high performing campaigns as a reference point, compare them to low performing designs and adjust the design identifying at the differences

Decrease in Conversion Rate (CR)

Possible Actions/RecommendationsExplanation
Configure Notification Display

CR might decrease if users lose incentive to convert due to an excess of campaigns displayed. If you have more than one onpage campaigns that can appear on the same page, you can enable this feature. Once enabled, it helps you set the number of screens per user in T time.

Create satisfaction guaranteed on cart abandonment
You can offer a satisfaction guarentee or extended return window to users who added items to their carts but did not purchase them. You can let them know that their purchase is a no-risk purchase to encourage them to check out. You can also use a timer in your promotions for a higher engagement rage and conversions.

Decrease in Incremental Revenue

Possible Actions/RecommendationsExplanation
Launch your use cases by using different Campaign RulesYou can trigger your campaigns based on condition groups. Campaign rules will help you select specific conditions your users can match with, and refine your audience.
Create an engagement for users with coupon codes

Coupon codes drive customers that are on the hunt for deals to purchase, and can even contribute to increasing the basket value. You can utilize Wheel of Fortune, Side Coupon, Page Curl and Scratch Coupon Templates.

Returning cart abandonersIf a user abandons their cart and comes back to your site, you can offer them a side promotion displaying what they left behind with a CTA that takes them directly to the checkout. You can make it easier to check out to encourage your users to complete the purchase.
Launch Social Proof campaigns for creating urgency on the usersSocial proof act as reviews, testimonials or social shares, and encourages users to take the same actions.

Decrease in Incremental Conversions

Possible Actions/RecommendationsExplanation
Use Campaign Trigger to sequence your campaignsYou can use the Campaign Trigger system to sequence your campaigns and trigger them based on how users interact with other campaigns.
Use templates with CTAs and pick the right wording and design for your CTA buttonsEffective CTA copy can easily communicate your offer, and drive users to take the necessary actions. 
Pick the template from Template Store based on your goals

Template Store helps you select a template based on the goals assigned to each template,

It is a collection of templates that you can use to create campaigns. This can be especially useful when there is a list of goals assigned to each template and you want to be able to customize them to fit the goal of the campaign. For example, if you have a different conversion goal other than purchases (e.g. lead collection, etc.), a template fitting these needs can increase your goal conversions.

Use enhanced goals like gageview and custom goals

Besides the default purchases and clicks goals, you can create your goals for different metrics you want to track.

Decrease in Impressions

Possible Actions/RecommendationsExplanation
Launch your use cases with different segmentsDelivering more relevant content to each group of recipients with the help of segmentation will result in an increase in open and click rates
 thus an increase in revenue.
Organize your mobile menu for better user experience

Category Optimizer provides a solution that allows users to create a personalized menu bar that enhances the user experience. You can manually or dynamically reorganize their menu listings and categories based on each user's data to improve navigation and reduce exit rates.

Arrange the placement of the campaigns for a better user experience

Just as you can customize the look and feel of your templates, you can also customize their placement and position depending on the page(s) you want to display your campaign. If you are receiving low impressions with a campaign, placing the campaign on a page/position that is more visible to users targeted based on your websites UX will help increasing impressions.

Decrease in Average Order Value (AOV)

Possible Actions/RecommendationsExplanation
Implement Purchase Progress Bar to increase Average Order Value (AOV)

You can create a Purchase Progress Bar to allow users to track their progress towards completing a purchase, reducing the risk of abandonment. It can also be used to incentivize users with added bonuses, such as free shipping or gifts, for staying on the checkout page longer.