In the world of digital marketing, data quality is the foundation of well-informed optimizations, accurate decision-making, and effective strategic planning.
But one hidden threat to the quality and integrity of your data is conversion lag - which can often lead to unnecessary panic and knee-jerk optimization decisions if it’s not understood and managed correctly.
In this article, we’re going to quickly recap the five dimensions of data quality, discuss the concept of conversion lag, talk about the implications it has on the quality of your data, and the steps you can take to fix it.
What is data quality?
Before we delve into how conversion lag can impact your data quality, let’s define what data quality is, and the factors that influence it.
There are typically five dimensions that you can use to measure data quality:
- Accuracy: Data should be correct and free from errors.
- Completeness: All required data should be present and no part of it should be missing.
- Consistency: The format and structure of data should be consistent.
- Timeliness: Data should be up-to-date and available when needed.
- Relevance: The data should be relevant for the purpose you intend to use it for.
If your data meets all these dimensions, you can have a high degree of confidence that it’s of high quality and is effective for making optimization decisions.
On the other hand, if your data doesn’t satisfy all these dimensions, it can lead to ineffective marketing decisions and misguided strategies.
Conversion lag has the ability to undermine the accuracy, completeness, timeliness, and relevance of data - so it’s not something that marketers should ignore, as it can significantly impact data quality and decision-making.
What is conversion lag?
Have you ever analyzed the performance data from one of your marketing channels, and wondered why the cost per conversion is higher for the most recent data? And how it seems to continually decrease as you look back over the last few weeks?
This is down to conversion lag, which is the amount of time between an ad engagement and a conversion.
For the majority of products or services, buyers don't typically decide to purchase immediately after viewing your video or clicking on your ad.
Buyer journeys are increasingly complex, and there's likely going to be a number of days before they decide to make their purchase.
Advertising platforms all report a little differently, but most typically attribute conversions back to the date an ad engagement occurred - not the day the conversion took place.
As a result, it can take days (or even weeks) to accurately report all the conversions that resulted from a specific marketing campaign. But frustratingly, at the same time, you’ll be reporting on the full amount of spend for the activity.
So, when it comes to reviewing the CPA or ROI of your marketing activity - having the full spend but not all the conversions can make recent performance look unfavorable.
Let’s assume there is a need within the business to look at the last 3 days ROI for marketing activity, compared to the last 3 months. The stats you present for the most recent performance are not going to look as strong. This can lead to inaccurate knee-jerk optimization decisions to try and address an issue that isn’t actually there. Performance is actually the same as it’s always been, it's just that incomplete conversion figures are causing data quality issues.
How does conversion lag skew reporting?
Conversion lag doesn't only have the potential to cause panic and inaccurate optimizations when looking at recent CPA or ROI figures - it can also lead to inaccurate comparisons between different marketing channels.
Let's assume you're running three different marketing campaigns:
- An email campaign, promoting a ‘flash sale’ for the next 24 hours.
- A generic paid search campaign, targeting users in the ‘consideration’ stage of their user journey.
- An online video campaign, designed to raise awareness of your brand.
Each of these marketing campaigns is going to experience conversion lag to different extents.
|
CONVERSIONS |
|||
|
Time from engagement to conversion |
Email Marketing |
Generic Paid Search |
Online Video |
|
1 day |
84 |
24 |
9 |
|
2 - 7 days |
12 |
27 |
23 |
|
8 - 15 days |
3 |
32 |
31 |
|
16 - 30 days |
1 |
17 |
37 |
The majority of your email customers will convert within one day, taking advantage of your time-limited promotion.
Customers clicking on your generic paid search ad might vary in terms of their time to conversion - some converting on day one, but others taking a little more time to complete their purchase journey.
And for those who have viewed your awareness video, you're likely to have caught them right at the start of their path to conversion - possibly prompting them to research and evaluate the market before making a decision. For this activity, a lot of conversions might come a lot later.
If you evaluate each of these campaigns after seven days, you'd be inclined to identify email as your best-performing channel and make optimization decisions on channel mix on this basis.
But this isn’t necessarily the truth - it's actually more the case that conversion lag is affecting the effectiveness of your analysis.
By corrupting the accuracy, completeness, timeliness, and relevance of your data - conversion lag can be a significant cause of data quality issues and damage your data integrity.
How can conversion lag be fixed to improve data quality?
The biggest issues with conversion lag occur when people aren't aware of it - blindly making incorrect optimization decisions after reviewing the last few days of performance data.
So by reading this article, you're already one step ahead of many - simply by understanding the impact that conversion lag can have on your data quality.
But there are practical steps you can also take to reduce the impact of conversion lag on your data.
The first step is to move away from only updating your database or reporting solutions with the last day of data. A better way is to look back a little further - continuously updating your historical data and renewing the last 30 days on every update, taking care to overwrite historical values for attributed conversions.
Another approach is to try and gain an understanding of how far conversion lag is actually affecting each of your marketing channels, so you're able to more accurately forecast what your future CPA or ROI might be when you're evaluating recent data.
While both of these approaches are effective in helping mitigate the impact of conversion lag on your optimization decisions, they are complex and time-consuming to implement manually.
Luckily, there are a number of data integration tools and data governance practices that can help you with this process, and improve your data quality.
The role of automated data integration and data governance in addressing conversion lag
By working with the right data integration platform, you can automate the time-consuming task of updating and overwriting your historic data to overcome the issue of conversion lag. By automating the process, it is less prone to human error and can be more frequently updated.
In addition, a lot of the leading data integration tools have built-in data governance features that can help you have more confidence in the quality and integrity of your data.
Want to find out more about how Adverity can improve your data quality management and help you overcome data lag?
Watch our data governance webinar, or book a demo today.
