--- title: "Fabelio Case Study: Merging Online and Offline Customers" canonical: "https://www.owox.com/blog/success-stories/fabelio" updated: "2026-10-22" --- # Fabelio found out what online customers are doing in their retail stores Updated April 15, 2019 · [Alyona Samovar](/team/alyona-samovar) · 6 min read · Ecommerce · [E-Commerce data model](/data-models/e-commerce) **ROPO** online-to-offline attribution built ![Fabelio found out what online customers are doing in their retail stores](https://cdn.owox.com/www/customer-success-case-study/fabelio/thumbnail/2-0yqhuy.png/public) The furniture multi-channel store from Indonesia named [Fabelio.com](https://fabelio.com/) decided to find out who’s the biggest fish in the pond and bring the most of profit — offline or online. With OWOX they got detailed ROPO report and improved their analytics. ## About Fabelio.com Fabelio.com is an online store for furniture and home decor. The company was established in Jakarta, Indonesia, in 2015, and is planning to expand to the Southeast Asian market. The [Fabelio.com](https://fabelio.com/about-fabelio) website has more than one million unique monthly visitors. [Track Ad Costs and Conversions in GA4 Easily link ad spend to GA4 conversion data to see your true marketing ROI. Get accurate KPIs and make better business decisions Start Free ![Track Ad Costs and Conversions in GA4](https://cdn.owox.com/www/webflow/6786518ebbeae26df45b303f_trial-ga-v2.svg/public)](https://www.owox.com/app-signup) ## The challenge Fabelio.com has ten showrooms where customers can see how products look like, touch the materials, test out furniture, and pay for their purchases. Fabelio marketers were keen to know how their online marketing efforts contribute to sales in offline stores and get answers to questions such as: * How long does it take for a customer to make a purchase decision? * How does this time vary by product category? * Which online channels have the greatest influence on the sales funnel at the last stages before an offline purchase? * Which furniture categories are most popular for online customers who make an offline purchase later? * How many website touchpoints do customers typically encounter before making a purchase? * How do all of these parameters differ for new vs returning customers? Fabelio.com salespeople write down the name, email, and phone number for each visitor to their showrooms. That’s why the company knows for sure when customers visit an offline store, even if they don’t buy anything. This is an additional data source. It also poses a new challenge: how to reflect this data in the sales funnel and determine which online source should be credited for these offline visits. ## The Turning Point OWOX Data Marts See your first report built in real time. _15 minutes._ 1. Connect your data warehouse 2. Pick your metrics 3. Get a live Google Sheets report In the time it takes to write a ticket. Then imagine never writing that ticket again. [Book a Demo](/book-a-call) We'll use your actual use case ## The decision To build smart analytics measuring the influence of online promotion on offline sales, the Fabelio.com team had to associate data on the activity of website visitors with data on customer activity in the showrooms. To build smart analytics, you need to choose a reliable cloud storage where all the data you collect will be aligned. For cloud [data storage](/data-storages), Fabelio.com chose Google BigQuery. BigQuery is the perfect choice for a company with limited resources: * It has flexible pricing and is relatively inexpensive compared to similar systems. * There’s no need to install any software on your servers or train your employees; basic SQL skills are enough. * It has plenty of ready-to-use libraries for working and integrating with other services. Fabelio marketing specialists established the following scheme for gathering data in Google BigQuery: ![fabelio data flow schema](https://cdn.owox.com/www/webflow/679573194aea61594f827366_40164.png/public) ### Step 1. Gather data on customers’ website activities To track events on the website, Fabelio uses Google Analytics (GA) — one of the most popular digital analytics systems worldwide as well on the Indonesian market. The company has an Enhanced Ecommerce funnel in GA: ![Enhanced Ecommerce funnel in GA](https://cdn.owox.com/www/webflow/67957370f7dfad29c4e4e262_30006.jpg/public) Aside from key interactions with the website, the Fabelio team tracks a variety of micro-conversions: ![A Google Analytics events report listing event categories with total and unique events, values blurred.](https://cdn.owox.com/www/webflow/679573702ec213d599bc3b0a_30007.jpg/public) This data helps them segment customers, explore the transaction funnel deeply, and estimate traffic sources accurately. ### Step 2. Gather data on expenses To estimate the impact of ad channels on sales, we need to compare the revenue and expenses for each channel. To gather data for this estimate, the Fabelio team established [automated importing of expenses](/import-advertising-costs-to-google-analytics-4) into Google Analytics with the help of OWOX Pipeline. With this expense data, Fabelio marketers can analyze KPIs for campaigns in Google Ads (which has a GA integration) and other services: ![A table of expenses by source and medium, with sessions, impressions, clicks, cost, CTR and CPC.](https://cdn.owox.com/www/webflow/6795736f86f1311919debe44_30008.jpg/public) ### Step 3. Import data from Google Analytics to Google BigQuery To import data on customers’ website actions and ad expenses into Google BigQuery, the Fabelio team used OWOX Pipeline. This service delivers the same hits to Google Analytics and Google BigQuery simultaneously. As a result, data is not sampled and is available for analysis in Google BigQuery just 2 to 5 minutes after it’s sent. ### Step 4. Import data from the CRM to Google BigQuery Fabelio stores data on customers, orders, and visits to showrooms in the Magento CRM. To associate offline and online data, Fabelio specialists established daily uploading of CRM data to Google BigQuery with the help of the [Fluent Plugin](https://github.com/kaizenplatform/fluent-plugin-bigquery). > _There are a variety of publicly available out-of-the-box solutions for integrating Google BigQuery with other systems. For example, OWOX has a few free scripts to integrate your CRM with cloud storage._ ### Step 5. Data processing After all data is gathered in Google BigQuery, it’s necessary to align it in one table. OWOX analysts helped Fabelio marketers to prepare a data set for online and offline orders with the [correct structure](https://support.owox.com/hc/en-us/articles/360003522373-CRM-data). ![correct structure](https://cdn.owox.com/www/webflow/6795736f4aea61594f82e3fa_30009.jpg/public) ### Step 6. Establish attribution At the final stage, the Fabelio team [implemented a ML funnel-based attribution model](/blog/articles/marketing-attribution-models) including offline orders. To work correctly, this special model needs data on offline store visits. To provide this data, Fabelio analysts prepared an additional [data source for attribution of custom events](https://support.owox.com/hc/en-us/articles/360002800253-Add-and-attribute-custom-events). ![The offline\_visit table schema, with time, date, category, client ID, revenue, cost and UTM fields.](https://cdn.owox.com/www/webflow/67957370f7dfad29c4e4e265_30010.jpg/public) To finish, the Fabelio team just had to launch the calculations. As a result, the company got a funnel that accounts for offline orders and visits: ![Funnel for Fabelio](https://cdn.owox.com/www/webflow/6795737009198266d2a46ed4_40150.png/public) ## The results Fabelio.com got automated reports that allow marketers to find insights and make the right decisions. Fabelio marketers now have access to the following insights in OWOX Smart Data: 1. Comparison of ad campaign value by different attribution models: GA Last Non-Direct Click and ML Funnel-Based Attribution by OWOX ![A bar chart of the change in values by campaign against Google Analytics last non-direct click.](https://cdn.owox.com/www/webflow/6795737054de51022a817016_40152.png/public) 2. Value distribution across sources and channels at different funnel stages ![Stacked bars by source and medium, split across the steps from visit to purchase, with a legend.](https://cdn.owox.com/www/webflow/679573709bd0ec05632e02d5_40154.png/public) In addition, OWOX analysts prepared an automatically updated [dashboard](/product/dashboards) in Data Studio for Fabelio. In this dashboard, Fabelio marketers can filter data based on source, product category, type of customer, place of purchase, payment method, showroom name, number of days from the first visit and first session, etc. The dashboard helps Fabelio marketers find answers to these questions: 1. How many website touchpoints does a customer typically encounter before making a purchase, and how profitable are those touchpoints? ![A donut chart of users by number of sessions, beside New and Returned bars and a table of orders and revenue.](https://cdn.owox.com/www/webflow/679573717234ef6d50957ab6_40156.png/public) 2. When was the first session of a client who has made a purchase? ![A column chart of users by first session date over several months.](https://cdn.owox.com/www/webflow/6795737229b6bb3cee64d51c_40158.png/public) 3. How many website touchpoints do customers encounter, on average, for specific categories of purchased goods? ![A table of session-count bands by furniture category, with bars for users and orders.](https://cdn.owox.com/www/webflow/67957370ac336004455ad648_40160.png/public) 4. How long does it take from the first website visit to the purchase within a given product category? ![A stacked bar chart of the top furniture categories by days from first visit.](https://cdn.owox.com/www/webflow/67957370cd073ae4e6d31c5b_40162.png/public) P.S. Our colleagues at Fabelio.com were encouraged to implement this solution after reading our article Omnichannel Retailing: Why and How to Integrate Online and Offline Customer Touchpoints. If this case study has encouraged you to look into integrating online and offline touchpoints, you should try building ROPO reports with the help of OWOX. You can experience all the possibilities of OWOX during a free trial. ## Your New Normal Turn your data into decisions. Governed data marts give you the clean foundation ML needs to actually work. * No AI hallucinations * Analyst-governed definitions * Every number traces to SQL [Get started free](https://www.owox.com/app-signup) ## Who wrote this ![Alyona Samovar](https://cdn.owox.com/www/webflow/6799099d337aa8a997b03b56_Alyona-Samovar.png/public) [Alyona Samovar](/team/alyona-samovar) Senior Digital Analyst Alyona Samovar is a Senior Digital Analyst who spent years at OWOX helping enterprise clients design analytics systems, build BigQuery reporting pipelines, and optimize marketing measurement. She specializes in SQL-based analytics, data modeling, and turning raw marketing data into actionable insights. Alyona writes about practical analytics workflows, BigQuery best practices, and data-driven decision-making. 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Where the page has a Markdown twin, its address follows the link. - [Alyona Samovar](https://www.owox.com/team/alyona-samovar) — /team/alyona-samovar.md - [E-Commerce data model](https://www.owox.com/data-models/e-commerce) — /data-models/e-commerce.md - [Track Ad Costs and Conversions in GA4 Easily link ad spend to GA4 conversion data to see your true…](https://www.owox.com/app-signup) - [Book a Demo](https://www.owox.com/book-a-call) — /book-a-call.md - [data storage](https://www.owox.com/data-storages) — /data-storages.md - [automated importing of expenses](https://www.owox.com/import-advertising-costs-to-google-analytics-4) — /import-advertising-costs-to-google-analytics-4.md - [implemented a ML funnel-based attribution model](https://www.owox.com/blog/articles/marketing-attribution-models) — /blog/articles/marketing-attribution-models.md - [dashboard](https://www.owox.com/product/dashboards) — /product/dashboards.md - [Case Studies](https://www.owox.com/blog/topics/case-study) — /blog/topics/case-study.md - [Marketing Analytics](https://www.owox.com/blog/topics/marketing-analytics) — /blog/topics/marketing-analytics.md - [OWOX](https://www.owox.com/blog/topics/owox-bi) — /blog/topics/owox-bi.md - [boodmo · Evaluating Acquisition Channels and LTV via Cohort Analysis · Ecommerce · Jun 27, 2017](https://www.owox.com/blog/success-stories/boodmo) — /blog/success-stories/boodmo.md - [Citrus · Competitors’ Prices Impact Sales: Citrus Success · Ecommerce · Mar 1, 2018](https://www.owox.com/blog/success-stories/citrus) — /blog/success-stories/citrus.md - [COMFY · Set up Marketing Analytics · Ecommerce · Dec 12, 2018](https://www.owox.com/blog/success-stories/comfy) — /blog/success-stories/comfy.md