I was recently discussing a strategy for A/B testing in the context of a business or marketing scenario, particularly around the time of Black Friday and Cyber Monday (BFCM).
And I suggested that the BFCM period is not suitable for testing due to the unreliability of results and potential performance sacrifices and therefore of ending all A/B tests and rather than experimenting to be leveraging the insights gained throughout the year to optimize your ads, offers, and sales funnels during this critical sales period.
This is a common strategy in e-commerce and digital marketing, where businesses focus on maximizing returns during peak shopping seasons by implementing their most effective strategies.
There are a few reasons why.
Skewing the Data of A/B Tests with Atypical Customer Behavior
Running A/B tests during high-traffic events like Black Friday and Cyber Monday (BFCM) will skew your data. These events are atypical in terms of customer behavior, traffic, and purchasing patterns, which are significantly different from the rest of the year.
1. Unusual Customer Behavior
BFCM events are known for influencing customer behavior in unique ways. Shoppers are typically more responsive to discounts, special offers, and the urgency created by limited-time deals.
This behavior is a deviation from their standard shopping patterns, affecting the usual Willingness to Pay (WTP) and rendering typical customer behavior data less relevant.
2. Increased Traffic
The surge in traffic during BFCM does not just mean more customers; it often means a different kind of customer. This period attracts a broader range of shoppers, many of whom may not fit into your typical customer demographic profile.
As a result, the influx of these varied shopper types can significantly alter the outcomes of A/B tests, making the data less reflective of your Ideal Customer Profile (ICP).
3. Seasonal Factors
The holiday shopping mindset introduces unique seasonal factors into the equation. The sense of urgency and specific motivations during BFCM can lead customers to make decisions differently than they would at other times of the year.
This shift can impact how certain elements of your website or specific marketing strategies perform, differing from their effectiveness during regular periods.
4. Performance Focus
In the midst of peak sales periods, the primary goal often shifts towards maximizing revenue and conversion rates. This focus detracts from the usual objectives of A/B testing, which is to gather data and experiment with new approaches.
The high-stakes nature of BFCM makes it less conducive to testing and more about capitalizing on known, effective strategies.
So, continuing A/B testing during such periods can lead to data that is not only unrepresentative of normal conditions but can also affect the accuracy and applicability of the test results for future strategies.
It's better to rely on tried-and-tested methods during these critical sales periods and resume A/B testing when customer behavior is more predictable and representative.
Therefore, you should retire all your traditional A/B tests over November and December.
What you could do now is test atypical customer behavior, traffic, and purchasing patterns.
But you might sacrifice performance…
A/B Testing Atypical Behavior
Testing atypical customer behavior, traffic, and purchasing patterns can be both beneficial and risky, depending on your objectives and the context of your business.
Let’s look at why you might or rather shouldn't engage in such testing of atypical customer behavior. In each example, we look at the rationale behind the decision to test or not, and a quick “how would one do it?” to provide a practical approach to implementing or avoiding these tests.
Reasons to Test Atypical Behavior
Whether to test atypical customer behavior depends on your specific business goals, the nature of the test, the potential impact on customer experience, and your willingness to accept the risks involved.
If the primary goal is to maximize immediate revenue, especially during high-stakes periods like BFCM, it might be prudent to stick with proven strategies.
Understanding Different Customer Segments
Testing during periods of atypical behavior, like holiday seasons or sales events, can provide insights into different customer segments that you might not encounter during regular business periods.
Testing pricing strategies during a holiday sale
During a holiday sale, you notice a new customer segment that is more price-sensitive and driven by discounts. By testing different pricing strategies during this period, you can learn how to effectively target this segment in future sales.
This period's unique dynamics, driven by discount-seeking behaviors, provide insights into how price adjustments affect sales volumes and customer engagement.
Implement dynamic pricing on select products and monitor sales data, customer demographics, and feedback to understand the price sensitivity and preferences of this new segment.
Preparation for Future Events
By understanding how atypical behaviors play out, you can better prepare for future similar events, optimizing your strategies for times like BFCM.
A/B testing the checkout process during BFCM
You run an A/B test on your website's checkout process during BFCM. Although this period is atypical, the insights gained help you streamline the process for handling high traffic volumes, preparing you for other peak periods.
High traffic volumes stress-test your website's capabilities, revealing potential bottlenecks or user experience issues.
Create two different checkout flows, randomly assigning visitors to each. Analyze conversion rates, time to purchase, and user feedback to identify the most efficient process.
Innovation and Experimentation
Testing in unique conditions can lead to innovative strategies and approaches that might not be apparent during normal conditions.
Experimenting with new flash sale formats
You experiment with a new type of flash sale during a holiday season, offering limited-time deals that change every hour. This test could reveal a highly effective tactic for engaging customers during future high-traffic events.
Unique sales models can engage customers differently, potentially increasing sales and customer retention.
Design a series of hourly flash sales with aggressive discounts. Track sales volume, customer engagement metrics, and social media buzz to evaluate the effectiveness of this approach.
Resilience and Adaptability
Learning how your business performs under unusual conditions can help in building a more resilient and adaptable business model.
Testing website load handling during unexpected traffic surges
During a sudden surge in traffic due to an unexpected event (like a viral social media post), you test your website's load handling capabilities. This helps you understand how to scale resources efficiently for future unplanned traffic spikes.
This helps you understand your site's scalability and resilience under stress, crucial for maintaining uptime during peak periods.
Monitor site performance metrics like load time and server response during the surge. Implement changes in real-time if needed and analyze the data post-event to plan for future scalability improvements.
Reasons Against Testing Atypical Behavior
If your focus is on long-term learning, innovation, and understanding diverse customer behaviors, testing during atypical periods can be valuable, provided it's done with careful planning and consideration of the potential risks.
Resource Allocation
Testing during peak times can divert resources from proven strategies that are known to maximize revenue and performance.
Allocating resources to a new marketing campaign during a major sale event
During a major sale event, you allocate significant resources to test a new marketing campaign. If this campaign underperforms compared to your traditional strategies, you might miss out on maximizing revenue during a critical business period.
This could divert resources from tried-and-tested strategies, potentially reducing overall effectiveness.
If you go ahead, balance the new campaign with proven strategies. Set clear metrics for success and monitor performance in real-time to make quick adjustments if necessary.
Unrepresentative Data
The data gathered during atypical periods may not be applicable to normal business operations, leading to potentially misleading conclusions.
Testing a new luxury product line during BFCM
You test a new luxury product line during BFCM and find low interest. However, this period typically attracts bargain hunters, so the test might not accurately reflect the interest level among your regular customer base.
The discount-driven audience of BFCM may not reflect the interests of your typical, possibly more affluent, customer base.
Despite the potential misalignment, if you proceed, carefully track sales data and customer feedback, keeping in mind the context of the event.
Customer Experience Risks
If the testing leads to negative customer experiences, it can have a lasting impact on customer loyalty and brand perception.
Implementing a new customer support chatbot
You test a new customer support chatbot during a holiday season. If the bot fails to address complex customer queries effectively, it could lead to dissatisfaction and harm your brand reputation.
Poorly functioning bots can frustrate customers, especially when they seek quick and accurate responses.
Deploy the chatbot while maintaining easy access to human support. Closely monitor interaction quality and customer satisfaction, ready to intervene if the bot underperforms.
Risk of Revenue Loss
During high-stakes periods like BFCM, experimenting with untested strategies could lead to significant revenue loss if the new approaches underperform.
Testing a new checkout interface during BFCM
If you decide to test a new, unproven checkout interface during BFCM and it turns out to be less intuitive, you might lose sales as customers abandon their carts due to confusion or frustration.
Any friction in the checkout process can significantly impact sales, especially during high-volume periods.
If you decide to test, ensure you have a quick rollback plan. Monitor key metrics like cart abandonment rates closely and be prepared to revert to the old interface if issues arise.
Conclusion
In conclusion, the decision to engage in A/B testing during atypical times such as Black Friday and Cyber Monday is a complex one, requiring a delicate balance between the desire for innovation and the need for stability and performance. While these periods offer unique opportunities to gain insights into different customer behaviors and test new strategies, they also come with significant risks.
The key is to approach these tests with a clear understanding of your business goals, the potential impacts on customer experience, and a readiness to manage the risks involved. For businesses looking to maximize immediate revenue, sticking with proven strategies during high-stakes periods like BFCM is often the safer bet.
Based on the analysis and insights gathered, it is evident that this period is not the most suitable for conducting A/B tests. The atypical customer behavior, unusual traffic patterns, and the general urgency of the shopping season create an environment where results from A/B tests are likely to be unreliable and not indicative of normal business operations.
Furthermore, there is a significant risk of performance sacrifices during this crucial sales period. Instead of experimenting and testing new strategies, businesses would be better served by leveraging the insights they have gained throughout the year. This approach allows for the optimization of ads, offers, and sales funnels, thus maximizing returns during these peak shopping seasons. Implementing the most effective and proven strategies, rather than venturing into the uncertainties of testing, should be the focus during BFCM.
This strategy aligns with common practices in e-commerce and digital marketing, where the emphasis is on applying what has been proven to work, especially during critical sales periods. By prioritizing stability and performance, businesses can capitalize on the heightened traffic and consumer readiness to purchase, ensuring a successful and profitable BFCM period.
