Scenario: a retailer has content targeting high-end products and low-end products. Does the content impact conversions? If so, how?
|We create three separate conversion paths. One for high-end content, one for low-end content, and one for all pages — this last one is meant to be a control group.|
|We connect each page view to a transaction to see how often that specific type of page view converts.|
|The analysis shows us that high-end content converts better — 53% versus 34%. On top of that, low-end content takes about 16.5 hours to convert, while high-end content takes just over 2 hours for conversions... Not only do we see more conversions, but they happen faster, too!|
Scenario: maximizing Average Order Value (AOV) is critical for ecommerce success. Which channels and acquisition tactics drive higher AOV?
|In this case, we are testing two types of strategies: Tiktok ads and special offers for a first purchase.|
|We split orders (i.e., transactions) into two types — those with a basket size above $60 and those below $60.|
|Our analysis shows that special offers convert with the same rates for low and high AOV transactions. Tiktok, on the other hand, generates 3.5x as many conversions (14.8% versus 4.2%) for transactions above $60.|
|We add a second transaction to see if there are any longer-term effects. Both high- and low-AOV transactions have the same conversion rate to second purchases. In both cases, the conversion rate is about 35%.|
Scenario: our ecommerce team is testing three types of promo codes: 5% off, 10%, and 25% off your first purchase. How do these promo codes affect first purchase conversion and long-term purchase frequency?
|We start by creating three purchase events, one for each promo code. The promo code is set in the "Event Settings" box in our platform.|
|Since we're interested in tracking how conversions take place over the long run, we add a second and third purchase component to the journey after the purchase made using the promo code.|
|We can already see that the conversion rate from first purchase to second purchase is very different for the 25% off promo code — it is nearly half of what the others are! Clearly, the long-term prospects of a 25% off promo code are not good.|
|The good news is that the conversion rates after the second purchase become the same across the board.|
Scenario: suppose our ecommerce team from the scenario above is also interested in seeing how promo codes affect refunds. Do promo codes affect refunds in any way?
|We add a refund event to the journeys we drew in our earlier scenario. Now when we run our analysis, we'll see how promo code transactions convert into refunds.|
|The analysis shows that our 25% promo code has over 8 times the refund rate as our 10% promo code, which has the lowest refund rate! Clearly, the incentives of the 25% off promotional code are not leading to the relationships we want.|
Scenario: the question of whether customer satisfaction drives LTV is an age-old and sometimes controversial one. With DataCX, it's easy to see the impact of customer satisfaction on purchasing patterns. Does customer satisfcation — in this case whether the customer is a promoter or detractor of the brand — affect follow-on purchases and LTV?
|We begin by building a journey starting with a page view, then a first transaction, and then a survey question that splits the path into those of promoters and detractors. Finally, we link the survey question back up to see how the conversions from each respondent impact follow-on purchases.|
|Our analysis first shows that there are significantly more detractors than promoters. Worryingly, 21.87% of purchasers become detractors, and only 6.5% become promoters.|
|More problematically, detractors have a significantly lower conversion rate to follow-on purchasers! Only 19.09% go on to make a second purchase, versus 54.7% of promoters.|