Redefining Customer Groups

  • October 5, 2018

Ofix Case Study – Overview

About Ofix: Ofix is a one-stop shop for office equipment and supplies. From stationery to furniture, the company offers a comprehensive range of office products that appeal to all kinds of businesses and individual buyers. It has quickly grown to become a premier source of office supplies in Turkey over the past few years.

Objectives: Due to the nature of its offerings, Ofix caters to both businesses and individuals. Although it had a well-optimized ad campaign in place, the company was running an ad campaign without optimizing it for different customer groups.

Our primary objective – lowering advertising costs without reducing sales by redefining customer groups and optimizing business-facing and customer-facing campaigns.

Final Outcome: Within 3 months, we saw substantial improvements in the Return on Ad Spend (ROAS). Thanks to continuous optimizations over these 3 months, Ofix’s ROAS shot up by an unprecedented 313.5%! That’s a boost of over 3x, in only a few months. What’s more. This metric is steadily improving even now.


The lack of a clear-cut strategy to identify and target B2B or B2C clients was our first challenge. This was especially critical because profit to the company for each B2B and B2C sale are wildly different. Hence, identifying and targeting the correct type of customer in our ad campaigns was paramount. But the search keywords used by both types of customers are very similar, so, this proved to be an interesting challenge for our team.

Our Hypothesis

An extensive analysis of user data and incoming search queries allowed us to hypothesize the following –

The basket (cart) value is a reliable indicator to identify whether a potential customer is a business or an individual.

While businesses are much more likely to be placing bulk orders, individuals will mostly place relatively smaller orders. We saw a way to use this metric to separate Ofix’s B2B and B2C ad campaigns for optimizing the ad spend.

Our Approach to the Problem

Even though we knew that the ad campaigns’ customer groups needed to be redefined, accurately and reliably identifying customers to achieve this required the use of several metrics and data –

  • Shopping Cart: As we hypothesized, enterprise customers were much more likely to make bulk purchases compared to individuals. Hence, shopping cart data was used as a key metric to identify the type of customer visiting the website.
  • Product Categories: Our analysis revealed that certain product categories were preferred by companies more often. Accordingly, the Boost Team used this as the second key metric to help bifurcate customer groups in the Ofix ad campaign.
  • User Search Query: Although search queries used by both businesses and customers were similar, we noticed certain product attributes within them, like number, size, and weight, were unique. Armed with this data, we grouped the attributes more likely to be used by businesses and customers to further optimize the campaign.
  • Product Profitability: Increasing ROAS by targeting more popular products is easy, but it might not elevate revenue due to lower margins. Our team kept product profitability in mind and targeted the products with the best margins to ensure that the Ofix ad campaign didn’t just witness a boost in ROAS, but that it did so in a sustainable fashion, which could further the company’s bottom line in the long run.
  • Product Attributes: User-behavior analysis revealed a startling correlation between certain queries and indecisive customers. Since these customers aren’t looking for anything in particular, we found that guiding them to products closely related to what they searched for improved conversion by helping them reach a decision faster.
  • Campaign Budget Allocation: We kept a close eye on the campaign budget during the optimization phase. During expansion and optimization, we noticed that the distinction between the B2B and B2C ad campaign was more pronounced on the weekends. Hence, the Boost Team set the campaign budget to change depending on the key metrics of ROAS as well as the day of the week.

Following performance metrics reliably required some technical creativity on our part.

Technical Challenges

The Boost Team created a self-updating, real-time dashboard on a Google Spreadsheet using the Google Analytics API.  This not only helped our team track the critical metrics that showed us both the health of the ad campaign and the effect of our optimizations, but it also gave Ofix easy access to all relevant metrics.


Over the past 3 months, Ofix’s Return on Ad Spend (ROAS) has shot up by over 300%, i.e. from a respectable 95.77% to an incredible 396.01%!

As seen from the graph, the growth is completely sustainable. What’s more, Ofix’s ROAS is still trending upwards due to our optimizations.


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