OWOX BI Updates That Will Level Up Your Marketing Analytics

OWOX BI is getting buffed up with a set of updates in all of the product family: Pipeline, Attribution, and Smart Data. Thanks to the active members of our community and our developers’ hard work, there are some major updates that we’d like to tell you about:

• ROPO reports in Smart Data that will help you find out how your online ad efforts contribute to offline sales.
• An improved method for collecting your session data and getting detailed info on the session sources.
• A referral exclusion list for collecting session data in OWOX BI Pipeline.
• A single partition table to better organize your data in OWOX BI Attribution, along with a new format for CRM transaction data.

ROPO reports in Smart Data

Window shopping online is a real thing! It’s more like common sense, as some customers are a bit worried that, for example, the products they order online may not match their expectations. That’s why they go to an offline store, check the products, and only then buy.

Thanks to Darjeeling’s experience, we know that such customers are often miscalculated or even not taken into account at all, when evaluating the performance of online ads. That’s why we’ve added ROPO reports in Smart Data to see how your online channels affect the offline sales. Moreover, you’ll understand which of your ad efforts were over- and under-evaluated, to invest in the campaigns that really work.

For instance, you can ask Smart Data to show the number of transactions from the first sources and mediums before ROPO purchases within a set conversion window, or learn how the ROPO revenue share changed by days.

Improved algorithm of collecting session data

For those who already collect raw data from a website with OWOX BI, we’ve upgraded the algorithm of session data collection. You can now get more accurate info about the actual session sources with the help of the Last Non-Direct Click model for the calculations in OWOX BI Pipeline. To do that, you’re able to use the new field trafficSource.isTrueDirect in Google BigQuery tables.

Let’s have a look at the example, to see how it works:

• On July 30th, a user comes to your website after clicking on a Google Search ad. In your raw data table, the field trafficSource.isTrueDirect for this user will have the FALSE value, while the source will be google/cpc.
• Later, on July 31st, the same user comes back to you by directly entering the URL in the browser. In your raw data table, the field trafficSource.isTrueDirect will also have the FALSE value. The source will be google/cpc too, as this user previously came to you thanks to an ad. The same will be for all of the following sessions of this user.
• However, if a user really came directly to your website, the field trafficSource.isTrueDirect will have the TRUE value, and the source will be direct/(none).

Referral exclusion list for collecting session data with the OWOX BI algorithm

Using third-party solutions for your website is quite common these days. This can be, for example, PayPal or another payment system. The only trouble is that you’ll see the payment processor’s domain as the source that brought you a new customer. Now, in OWOX BI, you can exclude this payment processor’s and other domains, by creating a referral exclusion list. It will prevent from rewriting a session source once a user is back to your website. Moreover, you’re able to copy the referral exclusion list from Google Analytics to OWOX BI Pipeline, if you created it earlier. In case you don’t have this list yet, it’s a good idea to produce it for both, GA and OWOX BI Pipeline.

A single partition table to make your attribution calculations more accurate and faster, and a new format for data about CRM transactions

The results of attribution calculations are becoming much faster, as all the data is now stored in partition tables in Google BigQuery. Now you get a single table that is updated with each calculation instead of a separate table for each of the calculation results. All of your data will now be carefully organized in partitions by time. With a single SQL query, you’ll be able to update and delete any records you need.

We’ve also freshened the data format for tables with the info on CRM transactions that you connect to OWOX BI Attribution. Now you can simply create one table to use it with all the OWOX BI services.

A quick sum up

1. Some users browse online to find the products they need, try and check them offline, and only then purchase. To know how many customers were brought to your bricks-and-mortar store by online ads, you can now use ROPO reports in Smart data.
2. A certain amount of users who came to your website directly could have actually been attracted by one of your ad campaigns. To find out which of your paid channels drove these users, we’ve added the Last Non-Direct Click model in OWOX BI Pipeline.
3. Using third-party services at your website for, say, payment, can distort your session source data by rewriting the original one. To avoid this, you can now create a referral exclusion list in OWOX BI Pipeline.
4. The attribution calculations are now faster and your data is better organized, thanks to new partition tables in OWOX BI Attribution.
5. You can now use a single table with you data about CRM transactions for all of the OWOX BI products.

Your opinion matters! Please vote for the features you’d enjoy in our products, or simply leave a comment down below.