How to increase ROI 2.5 times while cutting ad costs in half

Analytics Strategies Case Study OWOX BI

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Many businesses have a complex sales funnel, where it’s essential for the timely and accurate evaluation of advertising effectiveness, otherwise, the budget will be thrown down the drain. However, for medical projects the challenge of implementing a marketing analytics system, able to consider all customer touchpoints, is one of the most difficult tasks.

In this case, we describe the solution provided by the OWOX BI team for a clinic chain of family medicine, specializing in ambulatory medical care. There are 11 clinics offering telemedicine services to customers and providing medical treatment on the internet. The company is planning to scale this type of service, to make the brick-and-mortar clinics more of an addition to telemedicine.


Like most medical projects, the clinic has a complex multilevel funnel and gets about 80% of non-targeted traffic. Moreover, customers often interact with the clinic on multiple channels: online, on the phone, and offline. That’s why it’s difficult to evaluate the performance of the marketing channels, using only web analytics tools and standard marketing KPIs.

It was decided to set up a marketing analytics system to understand which marketing channels drive the targeted leads. The company’s specialists chose private individuals who come to the company themselves, not because of the insurance as the targeted lead.


The marketing team created two types of channels of their own: organic (not the organic type of traffic) and non-organic.

Organic channels are the ones that marketers can’t influence directly. Say, a patient came to the clinic as it’s close to his or her home, or as friends recommended it.

Non-organic channels are the ones that marketers can influence, controlling the channel efficiency:

  • Search ads.
  • SEO.
  • Marketplaces: platforms allowing people to find doctors.
  • Navigation services and place tags.

The clinic’s funnel consists of the following stages:

80% of all leads the company gets are phone calls. 85% of the callers go through the IVR stage. After listening to the voice messages some of the callers have to wait in line due to the lack of operators, usually, in the morning. 90% of callers go through the line in the second stage.

50-60% of people who talked to an operator, address the company to order service (stage 3). Others call to answer a question, learn about the pricing, etc. About a half of the 50-60% of the people who order a service, sign up for a doctor’s appointment (stage 4). Only 20% of such people actually get to the clinic (Stage 5).

Around 30% of customers who come to the clinic aren’t the target audience for marketers, such as the insurance owners. Finally, 60% of people, attracted by marketers’ efforts, are actually new patients (stage 7). As a result, only 8% of the new customers convert.

The cost is about $8 per phone call. Having such a multilevel funnel, the CAC is around $91, while the business margin is 20-30% on average. To improve the margin, marketers from the clinic decided to learn which channels bring the most targeted traffic, and invest in them more.


For starters, to implement the marketing analytics, it was needed to merge all the data collected and stored in different systems:

  • User behavior data from Google Analytics.
  • Phone call data from the call tracking service.
  • Data on doctors’ appointments, patients, and sales revenue from the CRM system.

The CRM system wasn’t the best option for merging data due to a set of limitations, like no API to import data from other systems. That’s why the company used Google BigQuery to collect together all the data via OWOX BI Pipeline as it’s affordable and easy to implement.

Below is the data flowchart of the clinic:

Now let’s jump into how the data goes around this schema.

Step 1. Collect user behavior data

The necessary metric system on the clinic’s website was implemented to get data on online user actions in Google Analytics. The specialists also set up OWOX BI Pipeline to send the user behavior to Google BigQuery as well, providing access to the raw unsampled data in near-real time.

Step 2. Merge the cost data

OWOX BI Pipeline also allowed the specialists to set up the automatic cost data import for the clinic. The data from Facebook is first sent to Google Analytics. Next, in Google Analytics, this data is combined with the Google Ads data (it goes to Google Analytics due to the native integration). Then, all the combined cost data is imported to Google BigQuery, where it can be merged with the user behavior data and the info on the actual clinic visits by patients.

Step 3. Take into account the phone call data

It works like this: someone comes to the website, sees a contact phone number (unique for each ad campaign), and calls the clinic. Once the call is over, the call tracking service provides the call source, medium, and keyword. As the call tracking system is already integrated with the clinic system, data on calls get to the clinic almost immediately, where it gets connected with the doctor’s appointments. Next, this data is automatically imported to Google BigQuery, via the Measurement Protocol.

Step 4. Build reports

Having combined all the data in Google BigQuery, the team configured reports in Google Sheets and Data Studio for the clinic. Using these reports, marketers can track the performance of all their ad efforts.

You can see an example of the high-level report above. The marketers use it to analyze the performance of the ad channels and certain campaigns within the channels. For example, over 1,000 CPC ads are divided into Brand, Geo, and Visit cards. In the table, you can find how much money is spent on each of the CPC ad groups and what results the clinic gets from them: total number and costs per a call, a visit to the clinic, and a new patient.

Marketers track all the channels, including direct visits to the website, and even have a special parameter for noisy calls (Code not working in the table above). If the call tracking system fails, and the phone number isn’t substituted at the website, such calls still get to the report. This way the phone call errors can be tracked and a timely reaction to the call tracking failures will be provided.

The marketers now carefully check every channel and build more detailed reports for the most effective and the least effective channels, should that be necessary.

The Data Studio dashboard allows to track the changes in the number of sessions, calls, and new patients across ad channels. Such a report also allows one to compare the total expenses with the cost per click, the total number of calls with the cost per call, the total number of new patients, and the cost per new patient.


  • Money saved. The implemented marketing analytics system helped the company change its marketing strategy. Now, the company doesn’t rely much on search ads and SEO, as these channels require a lot of resources, but can’t be scaled and don’t drive the desirable revenue, as seen from the obtained reports. Therefore the marketers stopped all the additional search ad campaigns, leaving only the most successful ones. Now, the clinic invests more into other channels that were underestimated before: navigation platforms that can bring good money. Also, there’s active testing of new ad formats with a smaller budget. As a result, the company boosted the ROI of certain channels by over 2.5 times and reduced the ad costs by two times, without any decrease in sales.
  • Better communication with the financial department. With the obtained reports on costs and revenue from ad channels, the marketers of the clinic can now approve the marketing budget faster and easier. This also helps build up a better relationship with the financial team.

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Top 30 handpicked Google Data Studio dashboards for marketers

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Top 30 handpicked Google Data Studio dashboards for marketers