Through data to goals: Setting up end-to-end analytics
In this article, we’ll explain what end-to-end analytics is and why it’s important for any company that promotes itself on the internet. Then we’ll show concrete examples of business problems that can be solved with the help of end-to-end analytics and describe the main steps of implementing it.
- What is end-to-end analytics, why is it needed, and what does it tell us?
- Problems of popular analytics systems, or why Google Analytics isn’t enough
- What opportunities does end-to-end analytics offer businesses?
- How to set up end-to-end analytics
- How to customize end-to-end analytics with OWOX BI
- Almost end-to-end analytics: collecting data in Google Analytics
- Useful links to end-to-end analytics case studies
What is end-to-end analytics and why do we need it?
In which advertising channels should you invest to get the most profit? This is the main issue that worries all internet marketers. Getting an answer to this question is like finding the philosopher’s stone: It’s not so easy, but it’s worth it.
To find out the real payback of online marketing in the context of channels and campaigns, you need to follow the user’s entire path, from clicking on an ad to paying for an order. And the more advertising sources you have and ways there are to make a purchase, the more difficult this task becomes and the more acute the need to implement end-to-end analytics.
End-to-end analytics combines data from all customer touchpoints and shows the profitability of marketing investments, taking into account completed sales, not just bids. To understand its importance, let’s look at the sales funnel of any e-commerce project in a simplified form:
Ad services→ Website→ Placing an order→ Your profit
Users come to the site from different channels, get acquainted with your product, and place an order by filling in an online form, sending a message by chat or email, calling, or going to a physical store to make a purchase. How can you understand which traffic source played the decisive role in a purchase made via any of these order/payment methods? What source should you credit for the value of the order if the customer has interacted with your company more than once and through different channels?
By default, Google Analytics gives all the value to the last indirect source (according to the Last Non-Direct Click attribution model), ignoring the contributions of other channels that participated in the sales funnel. Which isn’t entirely fair.
To find out the real value of traffic sources, you need to determine the contribution of each session before an order is placed. To do this, you need to take into account all points of interaction with a customer, including by phone, email, and offline. End-to-end analytics helps you solve this problem.
The second important thing that distinguishes end-to-end analytics from standard analytics is the method of accounting for sales. Some people who place an order on the site might not complete the purchase; that is, they might cancel the order, simply not pay for the order (for instance, if they’ve chosen to pay on receipt or using an off-site payment method) or might return the goods. Because of this, the number of orders in the web analytics system and the number of transactions in the CRM can vary significantly. It’s more accurate to evaluate advertising by profit and number of sales, not by order submissions and leads.
For example, say you run ad campaigns on Google Ads and Facebook for the same cost and get these results:
Judging by the number of orders received, it seems the Facebook campaign has shown good results. But let’s look at actual sales:
Google Ads brought in six times more sales than Facebook, and the conversion rate was higher. In this case, it’s more profitable to invest in the Google campaign and not in Facebook, as it seemed at first glance.
To determine the real effectiveness of marketing, you need to see how much money you spend on each channel, campaign, or keyword and how much profit you get from it.
Let’s summarize the main tasks of end-to-end analytics:
- Customize the collection of complete data for all touchpoints before the sale
- Supplement online data with information on actual sales from the CRM
- Evaluate the marketing return for each channel, taking into account all interactions with the buyer (not Last Click)
- Redistribute the advertising budget
The problem is that data on different customer touchpoints is collected in separate systems:
- In each advertising service, you can only see your expenses for that service.
- In popular web analytics systems (Google Analytics, Yandex.Metrica, etc.) you can see from where users come to your site, what they do there, and how many orders they place.
- Data on sales and returns is stored in the company’s internal CRM system.
To set up end-to-end analytics, all this information needs to be combined. In addition, if you have a lot of traffic and a lot of advertising campaigns, it’s important to automate the process in order to quickly receive the necessary reports and not have to produce them manually.
Problems of popular analytics systems, or why Google Analytics isn’t enough
To make an objective assessment of marketing efforts, you need to see the big picture:
- How much money you spend on attracting users
- How these users interact with your advertising and website
- How they place orders and pay
- How much real profit (not just clicks or leads) each channel brings you
Where can you get all this data? If your website has a Google Analytics tracking code installed, then half the battle is won. You can already find out:
- How many users each traffic source brings to your site
- What these users do on your site, including what products they view and add to the cart
- The conversion rate (the percentage of site visitors who complete a desired action, such as filling out an order form)
- The number of online transactions
- The number of sessions, the bounce rate, average time spent on a page, and other useful metrics
However, other information required for end-to-end analytics isn’t available in Google Analytics:
1. Advertising costs. Google Analytics doesn’t collect information about expenses for advertising services. If you don’t import this data yourself, you won’t be able to calculate and compare the ROAS for each channel.
2. Accounting for all customer touchpoints. If customers always completed transactions on the site, that would be perfect. It would be easy to relate each order to the source that brought it simply by tracking the user’s entire path. But in reality, people call by phone to clarify details or place orders, message by chat and email, go to offline stores, etc. Google Analytics doesn’t record these actions on its own. To get this data, you have to integrate with other services: for example, with a call tracking system that records all call data and links each one to a specific channel and user, then transmits this information to Google Analytics.
3. Execution of orders. In Google Analytics, you only see bids, not real sales. Customers can place an order, then change their mind, buy the product in another store, or return it. Also, Google Analytics often records test orders. As a result, revenue and transactions in Google Analytics may differ significantly from the real picture in your CRM system. It’s difficult to draw a conclusion about the effectiveness of an advertising channel if you don’t know what kind of profit it’s brought.
What opportunities does end-to-end analytics offer businesses?
When you collect data from all sources in a single system, you can analyze your marketing in more detail and increase its effectiveness. End-to-end analytics will help you:
- Automate the management of advertising campaigns. You can adjust spending by taking into account the ROAS for each channel, campaign, and phrase. As a result, you can reduce your advertising costs, as Santehnika-Online did.
- Create an automated report to analyze the marketing KPIs that are important for you: clicks, expenses, income, conversions, sales, ROI, etc. With an automated report, you can monitor metrics for advertising campaigns in real time and measure the effectiveness of all advertising channels on different platforms. You can also compare the effectiveness of advertising using different attribution models in order to find undervalued or overvalued campaigns and redistribute your budget.
- Find out which channels, campaigns, and keywords make a profit and which work at a loss. Based on the calculated ROI, you can then redistribute your budget to increase revenue. This is what Hoff and Answear did.
- Segment customers based on their buying activity. Then you can personalize communication with these customer segments in order to reduce advertising costs, extend the life cycle of customers, and increase the lifetime value (LTV) of your customer base as a whole.
- Perform ROPO analysis to discover how your online marketing affects offline sales. End-to-end analytics will also help you understand why your customers are looking at products on the site and buying in a physical store and find out what prevents them from ordering online.
- Conduct cohort analysis to calculate LTV and understand how to increase this indicator.
- Conduct A/B tests of various advertising campaigns and channels to identify the most effective. For example, marketers for OnlineTours conducted an experiment to compare individual offers by phone and email. As a result, they managed to increase their conversion rate for emails to 15%.
How to set up end-to-end analytics
There are quite a few ways to set up end-to-end analytics, but the goal is the same: combine data from Google Analytics, advertising services, call tracking systems, and a CRM. You can accomplish this with various tools and by collecting your data in various places.
Choose a method based on your company’s capabilities and business objectives: Is it enough for you to see expenses, income, and ROAS for each channel? Or do you want to build custom reports in the context of dozens of other metrics that are important to your business?
Our marketing checklist will help you set up end-to-end analytics correctly and without problems, no matter what method you choose.
Method 1: Configure end-to-end analytics with OWOX BI
This method is ideal for companies that want to carefully analyze their data. OWOX BI integrates data from all sources in Google BigQuery cloud storage. With OWOX, you can build reports on complete unsampled data using any combination of parameters and indicators.
Benefits of end-to-end analytics with OWOX BI
- All user actions are transmitted to Google BigQuery directly from the site, in real time, without prior processing, with hit-level accuracy.
- Get uncomplicated, raw session data, regardless of the number of site visits.
- Collect and process customers’ personal data, including email addresses and phone numbers.
- See how much each session costs you: ad spending is transferred daily from Google Analytics to BigQuery and distributed into sessions according to UTM values.
- With the OWOX User ID, you can analyze user behavior across your sites, even if they aren’t linked directly. An additional identifier will help bypass the limitations associated with Google Analytics’ Client ID, User ID, and cookie storage time.
- You don’t need to purchase expensive software, licenses, or equipment. Data is stored in your Google BigQuery project and access to it is controlled by you.
Basic configuration steps
- Set up site collection in Google BigQuery using the OWOX BI Pipeline.
- Combine cost data from various ad services into Google Analytics, then upload that data to Google BigQuery.
- Import call and email data from your call tracking system and email newsletter system to Google BigQuery. Some services support direct integration with OWOX BI.
- Upload data on revenue, purchases, and returns to BigQuery from your CRM system.
- Build reports in Google BigQuery using SQL queries, or use ready-made reports in OWOX BI Smart Data simply by entering metrics in the search bar:
- Visualize data in a convenient interface for you: OWOX BI Smart Data, Google Data Studio, Tableau, Microsoft Power BI, Google Sheets, or something else.
A data collection scheme using OWOX BI looks like this:
OWOX BI has a free trial version. Subscribe and set up your end-to-end analytics system.
You can build a useful and informative dashboard like this:
Method 2. Almost end-to-end analytics: collect data in Google Analytics
This method is suitable for companies that have a relatively small amount of traffic, few orders placed by phone, and minor differences between the number of purchases in the CRM and in Google Analytics.
In addition to saving money, this approach is easy to implement. In Google Analytics help, you can find comprehensive instructions on how to import data on expenses, products, sales, and returns.
The disadvantage of this method is that the data in your reports may be sampled, and there are restrictions on the number and combination of parameters and indicators in one report. In addition, if you manually upload data on expenses and income to Google Analytics, you need to do this every time you need a report. This isn’t critical if you have two or three advertising channels and you need data once a month, but it becomes a problem when you need to analyze hundreds of campaigns daily.
Basic configuration steps
- Put UTM tags in all links from your ad campaigns so Google Analytics collects accurate information about traffic sources.
- Set up advanced e-commerce tracking.
- Install a call tracking system on your site and integrate it with Google Analytics.
- Transfer the Client ID to your CRM system together with an event, for example when a customer fills out a form on the website, makes a call, or writes in a chat. You can link all your data using this identifier.
- Import expenses from all your sources into Google Analytics. This can be done manually or automatically using OWOX BI.
- Set up the transfer of revenue, sales, and returns data along with Client ID to Google Analytics via the Measurement Protocol.
As a result, you’ll get something like this report:
Each case study on our blog concerns end-to-end analytics in some fashion. Here’s a selection of the most interesting success stories of OWOX BI customers:
- Discover how MatahariMall combined all their data in a single automated report to save time and properly reallocate their marketing budget.
- Rendez-Vous success story: Online influence on offline purchases (identifying the ROPO effect)
- How INTOUCH built an effective advertising campaign evaluation system
- Boodmo and OWOX BI: How to evaluate customer acquisition channels using cohort analysis