VMAs: Valuable Marketing Assets
As much as I like music, I am sorry to disappoint you but this blog is not about the Video Music Awards. We will not be talking about Justin Timberlake’s reunion show with NSYNC or why Daft Punk didn’t win the best song of the summer. Instead we will discuss how to evaluate your marketing channels in terms of the assets they bring to your business and how all this is possible with Adobe Analytics Premium.
We will consider that all your channels are already setup correctly in Reports & Analytics. You have identified the channels such as Email, Paid Search, Display, Social, Natural Search…. and set the proper guidelines in the Marketing Channel Processing rules under the Admin Tools. If you need a refresher, check out this series. For the sake of this post, we will concentrate on two channels (Display and Paid Search). Through Genesis Integration, you are able to bring in Display and Paid Search impressions/clicks/cost data and put them against conversion metrics in your reporting. You are able to look at how well your campaigns are doing. How do we define “well”? This varies from one business to another but for simplicity we will consider that high conversion/transaction rates means “well”.
Looking at this in terms of an example, let’s assume that your business is a Music Store called “House Music Store (HMS)”. HMS is an online store selling electronic music and production plugins. HMS is fully aware of the importance of the digital presence and therefore spends a considerable amount of their yearly budget on display and paid search campaigns. Through 3rd party vendors, HMS is able to look at impressions/clicks/spend metrics side by side to the transactions metric associated with these campaigns:
You are happy to see that your display campaigns are costing less but resulting in higher transactions and in return making you more $$$. This prompts you to consider adjusting your spending in next year’s budget planning; you decide to spend a little more money on Display campaigns and a little less on Paid Search. This is a valid way of looking at increasing your profit but what happens if in reality Paid Search campaigns bring you high value customers spending $100+ per month while Display campaigns attract one-time buyers spending less than $10 per year? This means shifting your budget towards Display might not be the best move as you will miss out on the opportunity of reaching out to high value customers.
This is all great but first, how do you identify high value customers? Second, once identified how do you link these customers to the marketing channels to measure their success? Don’t you worry, we got you covered and this is where Data workbench comes into the rescue. All your customer information exists in your CRM database. Every time a customer signs up online, a unique customer ID is generated. In the back end system, you have a database relating the customer ID to a list of transactional attributes such as the account ID, transactional ID, total money spent and more. This will be similar to this table:
Now we are looking at two sources of data, 1) The Web data collected by Reports & Analytics and 2) The CRM data stored in your back end system. As the account ID is a common key between CRM and the WEB data, we can leverage the Unified Customer Process in Data Workbench to tie these records together and roll them up to a top level key, i.e. customer id. Doing so, not only you are able to tie a customer’s web behavior and offline attributes together but also distribute your customers into different bands. Based on these bands, you can build a visitor/customer level segment to bucket them accordingly. In this case, we chose 4 bands:
The final step is to develop some customized metrics to match the tiers in the Customer Bands. For example,
High Value Transactions = Transactions [Customer Bands = “High”]
Mid Value Transactions = Transactions [Customer Bands = “Mid”]
Now you are ready to look at your Marketing Channels again. This time, you can look a little closer on your transactions in terms whether these were high value transactions or a one timer:
This model can be easily extended to other metrics within your dataset. This can be applied to new accounts, attribution models and more. This will give you a broader view of the value of each marketing channel and the assets it brings to your business.