As someone who has used online customer data extensively in multiple roles and at multiple companies, I really believe most companies are respectful in their use of customer data and are attempting to improve the customer’s life. I tend towards sharing my own data with companies that request it that I respect and have a relationship with. Perhaps for me especially that is why it is so difficult to hear that this extremely personal data was being taken without knowledge, consent, or request – and used for purposes undefined.
I found this to be a very blunt and honest warning of why Data Projects can fail. It’s a good (if pessimistic) read for anyone who is running or planning to run a data science project within their company.
I’ve mentioned before that click-through rate (or CTR) isn’t the only method for measuring a marketing campaign. While it’s a useful metric, focusing on it without considering other ways a campaign is performing might not give you a complete, accurate picture of what’s really going on.
In part one of this video, I explained that the goal of the campaign is very important to an understanding of the results because they can impact the measurement drastically. But just as a refresher: Would you use the same measurement for a campaign whose goal was to increase sales and checkouts versus a campaign whose goal was to introduce a product? For the first example, you’d look at the people who were served a goal and determine if their sales and checkouts increased to determine if your ad was successful — whereas when introducing a product, you would see if they explored the product area of your website, searched for the product, discussed the product with a sales representative, or downloaded material about the product. The goal of the campaign is critical to determining overall success.
But there are still more options for evaluating how well a campaign is doing it’s job, and the two I touch on in this video are:
- A/B testing
- Marketing Mix Modeling results – Sales impacts in comparison to other campaigns (isolating for other changes to the business)
While multi-billion dollar companies often use marketing mix models — advanced modeling that attempts to isolate changes from a campaign from other impacts to the business, and derive a revenue impact — most companies are content with A/B testing to determine if their marketing is incrementally improving. In A/B testing, you measure two ads (or creatives or other marketing elements) at the same time (sending customers to one or the other randomly) and compare their performance. It is a very useful approach to attempt to determine if a proposed ad is better than the current ad and allows a business to analytically improve their approaches.
In the end, CTR is only one measurement to help measure the success of a campaign and as our industry grows in its intelligence and customization of marketing campaigns, we will need more than just CTR to determine if a campaign is successful or not.
This content was created per request of Multiview and included in their blog posting. Please see the resulting interview and original post here.