Closed-Loop Analytics

The term closed-loop analytics is very descriptive. It reveals the path or process closed leads follow from the moment they land on your website as visitors to when they become a customer. Closed-loop analytics essentially closes the loop between marketing and sales data because all the information from start to finish is accessible on one platform. 

Marketing and sales teams use the information from closed-loop analytics to boost conversion rates all around.

Gaining insight into how many leads are generated by a marketing campaign is the tip of the data iceberg. With closed-loop analytics, marketing teams can learn much more about the value of their campaigns and how to improve them. 

Closed-loop analytics helps a marketing team:

In order for all this to be possible, the marketing team needs a way to access sales data, and unfortunately, that data isn’t always readily available.

The general customer lifecycle goes something like this:

As the lead moves through the customer lifecycle, there’s a division between the marketing team and sales team. The marketing team uses an analytics tool like Google Analytics to gather data on the first two stages, including where the visitor comes from. However, in the third stage (MQL to customer) the sales team usually logs information in a CRM system.

Often these two tools/systems are completely separate and the data isn’t aggregated. The data is disjointed, telling the marketing team about their leads but failing to provide follow-up on what becomes of those leads. 

Bridging the gap with closed-loop analytics that shares the sales team data with the marketing team is highly beneficial to both groups. Understanding what happens after the sales team takes over allows the marketing team to target campaigns and deliver more MQLs.  

Much of the data marketing teams collect is at the beginning of the customer lifecycle. They can figure out how many users clicked a Google Ad or responded to a Facebook campaign, but that only gives you a look at part of the picture. 

That front end information doesn’t always tell you what users did once they got to a landing page. It doesn’t tell you if your marketing campaigns attract highly qualified leads or a lot of traffic that doesn’t continue down the sales funnel. 

That’s where closed-loop analytics come in. It fills in the gaps, telling the marketing team what visitors do deeper down the funnel. Knowing what steps these users take is extremely valuable for marketing teams. It can help marketers zero in on who the most highly qualified leads are and what motivates them to take action. 

This information can be used to create marketing campaigns that target users who are more likely to become customers and direct them to the most appropriate part of the sales funnel.

Let’s take a look at mock scenario to highlight how closed-loop analytics can be used by a marketing team: 

Your marketing team is promoting a car air freshener system. A Google PPC campaign is created that promotes the low price and longevity as key benefit points. The campaign brings in 1,000 leads in the first week. That’s what the marketing team can easily gather from their metrics. 

They may also be able to tell 750 of those leads don’t make it past the landing page, and only 25 leads made a purchase directly from the landing page. 

Closed-loop analytics provides the answer to what happened with the other 225 leads. Fifty of the leads checked out the fragrance selection page. Half of those leads decided to buy the freshener system, and the majority selected either the pine fragrance or cherry fragrance.

The remaining 175 leads requested more information on the air freshener system. The sales team follows up with each lead. They discover the number one question that the leads have is whether the air freshener system will affect the use of their air conditioning system. After the leads are reassured it won’t affect air conditioner use the sales team is able to convert 70% of the leads into customers. 

Because closed-loop analytics is used, the marketing team is able to extract three main takeaways from the data collected by the sales team: 

By analyzing data that’s gathered further down the funnel the marketing team can improve the ad messaging and landing page to increase the conversion rate. Ultimately, the ROI of marketing campaigns goes up while the cost per acquisition goes down.

Closing the gap between the marketing team and sales team is actually a lot easier than expected. You can go the manual route and pull information from multiple systems to analyze data from campaign launch to conversion to customer acquisition. It’s time-consuming, but it’s possible. 

The other option is to use software that can bring all the information together on one platform. Ideally, you want to implement audience-tracking software that can track individual user actions from the first visit all the way through purchasing. With Mixpanel analytics software this type of conversion tracking can be done by establishing Events and including Event Properties. Funnels are also useful for tracking the steps a lead takes to become a customer.

Software that tracks each individual is much more insightful than software that aggregates user information. This is one of the shortcomings of Google Analytics. Without the capability of tracking individual leads, it’s difficult to determine the specific characteristics and behaviors of MQLs and the marketing tactics that attracted them in the first place. And without going one step further and bringing in the sales data for individual users, the marketing team can’t determine which keywords, traffic sources, etc. generate leads that don’t buy versus leads that do buy. 

With closed-loop analytics reporting in place, the marketing team is no longer optimizing campaigns for traffic. They are creating marketing campaigns to optimize conversions and sales, which is far more beneficial for the business’ bottomline.