Tracking important business actions that happen beyond your website or application is a critical step for businesses in a disruptive industry. It’s one of the best ways to reduce your CAC, which is a top focus of disruptive companies looking to rapidly grow in a slow moving industry.
Event & Session Tracking
Event tracking allows advertising platforms like Facebook and Google Ads to understand what people do on our website or app after they click on a paid advertisement. In order to do this accurately, these systems need the ability to store and work with a reliable session, which is basically a way for them to associate events with a person that clicked an advertisement. Without a session, events aren’t tied to any specific person or individual.
To track these sessions, most (if not all) of these platforms track first-party cookies in your browser. These stay there until a person clears their browser cache, or if they’re using a private browser tab, until they close the window. However, when an individual creates an account or otherwise willingly provides a way to be uniquely identified, a persistent session can be created that is longer term.
This persistent ID for a customer or individual is commonly referred to as a user_id, and it allows marketers and advertisers to more accurately track important business actions at an individual level. This provides a much better aggregate understanding of the ROI for paid advertising clicks and visits.
Automatic Advertising Optimization
If you run an eCommerce business where transactions occur online, then you’re in a fortunate position. Your business is able to track purchase related conversion events and feed this information directly to advertising platforms. When platforms like Google Ads and Facebook receive this data, they’re able to understand that a person (or session) bought a product and made your business money.
When set up correctly, purchase events will contain detailed information like quantity, price, revenue and profitability. Ad platforms receiving this information now know which individuals have clicked on your paid advertisements and become a paying customer.
Using this insight, ad platforms are able to analyze the vast and deep profile they have on that individual to identify common traits and patterns about the person. This could include anything: age, weight, height, health, income, location (city/state/zip), and so much more.
If you feed in robust data in the correct format, they can understand key performance details about the sale, including:
- How much profit you made from the customer in the sale
- How many purchases has this customer made over time
- Who your most valuable audiences are so that you can automatically target and reach them in new ways
Optimizing your ad bidding, placement, keywords and audience selection based on events that are tied directly to profitable business events is how the most successful companies are spending their ad dollars online today. It can be difficult to get setup, but when you work with someone that knows how to do it correctly and in ways that are stable long-term, it can result in phenomenal results.
Offline Conversion Events
But what if you don’t sell traditional products online? Most businesses I’ve worked with don’t, and it’s not uncommon for transactional information related to customer purchases to be in a seemingly unobtainable location from a marketing and advertising perspective. It makes a lot of sense for this data to be locked down, it’s been an IT standard for decades and for good reason: leaking information about your customers and their purchases could be detrimental for a business. I believe this is what keeps many businesses from working with offline conversion events: the data is simply too difficult to get to and work with.
Disruptive companies are finding ways to do this, and it’s working incredibly well in the few instances I have seen and analyzed. When you find reliable ways to feed offline transactional information into advertising software, you’ll open the door to untapped opportunities that are both significant and substantial. This is particularly true for businesses with long sales cycles, and long buying journeys. It only works when you have a consistent, must have, key ingredient: a solid connection with the web session that interacted with your paid ads. Without this, your advertising software won’t be able to associate any paid ad clicks or visits to your website with the offline purchase.
Why Does It Matter?
Cost per acquisition. Tracing your paying customers back to the dollars you spent on them directly allows you to automate the way you spend future ad dollars. You can create proactive bidding strategies to attract the most valuable potential prospects. When it’s done correctly, your cost per acquisition should drop substantially. This will allow you to stretch your ad budget in new ways you aren’t today.
Here’s a real-world business example:
- You spend an average of $6078.86 per day on paid advertising (based on a 10-year average)
- You close an average of 17.23 paying customers each day
- Your cost per acquisition was $352 per customer
Depending on your profitability per customer, this could be wonderful or terrible. Even if it is wonderful, it should (most likely) be a lot better when using the approach I’ve outlined above.
What if your cost per acquisition was under $100? When companies are optimizing their ad spend against true purchase conversions, their acquisition cost should rarely if ever be above $100. This depends on the industry, the average deal size, and other specifics, but it’s a good general rule that applies to almost ever case I have seen.
Here’s the same set of numbers mentioned above, but with an adjusted acquisition cost of $100:
- You spend an average of $6078.86 per day on paid advertising (based on a 10-year average)
- You close an average of 60.79 paying customers each day
- Your cost per acquisition was $100 per customer
Effect on Business Performance
If we know what the average profit per customer is, we can draw some valuable conclusions from this information. Let’s pretend that each customer in this scenario provides an average of $1000 profit:
- The original numbers would yield a projected profit of $17,230 each day
- The adjusted numbers would yield a projected profit of $60,790 each day
Annualized, that’s a difference of $22,188,350 a year, or $6,288,950. It’s worth the investment and makes a difference, which could very well be beyond what is shown here. Many businesses run average acquisition costs of $50-75 per customer. It’s entirely possible when you’re able to automatically target prospective customers that are algorithmically likely to be interested in purchasing your product(s).
It makes a lot of sense as an approach, and it’s one of the things I really enjoy helping businesses do.