How to Scale Your eCommerce Business: Apply the Conversion Framework

Over the last decade, we have worked with +20 eCommerce companies in Europe and APAC. One of our goals has been to create a methodology, an approach that can be applied to any eCommerce company — independent of their industry.

Over the years, we have developed and successfully applied a model called the FALCON Conversion Framework. This framework will help you as a Chief growth/marketing/digital officer to grow your business. It has helped multiple other high-growth companies globally already.

The conversion framework exemplifies how marketing effectiveness, consumer touch-points, product & service offering are interconnected. That if you change one part in one area that it will have a planned (or unplanned) impact on another. Build on the right measuring framework (with performance data and consumer insights) you can apply the conversion framework with a goal for continuous improvement.

We first started to develop this thinking during my time at DailyDeal (which got acquired by Google Inc. in September 2011) but have only started to refine and apply it on multiple clients at FALCON.

By working on a lot of successful (and not so successful) companies and brands, we have learnt that there is not a single silver bullet but there are countless small improvements that will add up for a big win.

THE POWER OF THE CONVERSION FRAMEWORK

Firstly, why do we think that the conversion framework is so powerful? Because it helps to align teams and departments towards one star KPI: conversion. More conversions. But to get there you have to learn WHY and especially WHERE you face challenges.

Before we jump into the conversion framework, let us deep-dive on WHY we needed a new model. Typical (marketing) models are usually simplified or flawed. They are only looking at marketing effectiveness. Or looking at User Interface (UI) or User Experience (UX). Or from a product/service offering a view in terms of how we can be more competitive with better, faster, cheaper services and offerings. So most models do not have a holistic measuring or a framework.

As you can imagine, these models missed out on essential parts from a consumer journey or they looked purely on a subset of it without considering the dependencies and consequences. You can run a simple example on your existing marketing model and check whether you can find needed data-points at once: What was the impact of a campaign A on a user segment B that browsed through a tablet/app but converted via desktop with a discounted offer on a product that was on sale on Tuesday with delivery within 30minutes? If you don’t have an immediate answer then you should consider using the FALCON Conversion Framework.

The conversion framework is a tool which is based on quantitative and qualitative data points aiming at continuous improvement. With a focus on generating more conversions. And with an ultimate objective to align the organization towards this star KPI.

The conversion framework improves your performance as you start looking from a more holistic view on the consumer journey. Without a holistic analytical framework you tend to oversimplify it. Or focus on a specific part of the journey only (e.g. How can we improve step 4 to 5 in an on-boarding process). Don’t get me wrong. These things are important. But working in silos and not looking at it from a holistic view, it will be very challenging to understand where the bottleneck is located in your consumer journey.

Let’s jump into the FALCON Conversion Framework:

1. Foundation: To make the best out of it, you have to make everyone understand that this is an analytical, data-driven framework. Our approach should be ‘what you can’t measure, doesn’t exist’. There is a high probability that you can always track an interaction with a brand. Yes, it might not be 100% accurate all the time but there are always (creative) ways to track something. Or at least to think about ‘how can we track this’.

a. Example: At DailyDeal we were able to track our TV performance and its impact on our SEM ads as we structured the content of the TV spots with 3 main keywords in the plot of the TV spot. When there was a TV flight we saw a spike for these 3 specific keywords (and/or a combination thereof) in our Search volume and we were able to identify which user segment responded best to which TV campaign (on which TV channel & time). Back then it was not possible to link the TV performance with your SEM performance (which you can do nowadays). So we tested and saw that we can track something that we deemed as ‘valuable’ information (and also to identify the right TV channel and TV flight mix for our adjusted customer acquisition cost).

2. People: You will need someone in the organization who ‘owns’ this model. This is usually a Chief Digital Officer. He will make sure that you have your weekly meetings with the relevant C-level or Heads and he has to ensure that there are a proper preparation and follow-up of the meeting. He will also document the test’s/activities that should run. In this weekly meeting, you will also need the people who are responsible for marketing effectiveness (CMO), consumer touchpoints (your Chief Product or Experience Manager) and service/product offerings (your Chief Operating Officer). It is not only important to get their buy-in for each test/activity but also that they know WHY you are running certain tests or initiatives and that they can bring it back to their teams for execution. In the best case scenario, you can get everyone aligned (Example a). In the worst case scenario you get totally frustrated (Example b):

a. Example: At FoodRunner (which got acquired by foodpanda), we took an interim-CMO position and were responsible for the weekly Conversion Framework meeting with our Chief Operating Officer (COO) and our Chief Product Officer (CPO). I collected all the relevant data points by Monday (or requested more qualitative data-points) and we scheduled our meeting on TUE morning and first looked at the impact of our activities from last week and defined 2–3 new tests or activities for the following week with a clear focus based on one of the bottlenecks we have identified. One of the most under-valued but in fact high-value activity is to look at great(er) length WHY something has worked or not. And to document it 🙂

b. It can be also very painful: we worked with an F&B chain and their eCommerce arm to scale their activities in APAC. Unfortunately, we had a super slow (and seemingly incompetent) web development partner on board. It took literally weeks to get things running. And when we were running a test or experiment there was a 50% that there was a problem because of this web development partner. So the ‘alignment’ of the 3 departments (marketing effectiveness, consumer touchpoints, and service/product offering) is KEY.

3. Collection: The ‘measuring & analytics’ part is the basis of this activity. If your tracking and/or data-set is bad. Yes, then all the hard work around it will be worthless. So make sure that you set-up your tracking tool, with a proper naming convention (which is mandatory to use for every internal & external marketer and partner!) and get your BI/Datawarehouse system in shape so you don’t need days (or even weeks) to gather specific data points. Apart from the performance data (which is usually comparatively easy to gather), the other important part is the qualitative input/data points.

a. Example: At FALCON, we helped to scale one of the fastest growing F&B chain’s eCommerce store. Apart from most of the marketing effectiveness and consumer behaviour-data we also conducted a weekly qualitative ‘mystery shopping’ test. This helped us a couple of times to identify bottlenecks in the consumer experience and/or in operations and tackle it first hand to improve conversions (and especially retention through better service levels!)

4. Process: Now the fun begins, first, you will look at the consumer journey and start to identify WHERE did it slow down the conversion. You start looking at the marketing effectiveness (your user acquisition, activation and retention activities) and deep-dive on specific user segments and look at their behavior. The goal is to identify patterns: You want to identify a pattern for a specific segment (or even micro-segment) and think about your proposed course of action. This proposed course of action will be your first test for this coming week. This process is repeated until you have developed 2–3 tests for this coming week and DOCUMENT it. Documentation is key as you not only refer to these tests but knowledge starts to get externalized. And everyone can be easily on-boarded on previous (and upcoming) activities.

a. Example: At FoodRunner, we saw that a specific cohort has behaved strangely (aka did not convert). They browsed a lot of pages, looked at a handful of restaurants, even put different food items in their basket but at the end they did not convert. After a test, we realized that the longitude setting of a specific area in Malaysia was set wrongly and they automatically got a 15% higher delivery fee. (There was an ops & finance logic behind the higher delivery fee for certain areas). Which stopped them from ordering. By changing this requirement for this specific area, we saw an uplift of +50% of conversions for this cohort. In retrospect, it sounds logical but in reality, we needed the buy-in from the product (to change the delivery algorithm) and operations (to be able to deliver within 30min in this area). We documented this learning in a shared lessons learned document and put an annotation in our tracking tool of what we changed that sparked this uplift.

What I personally like most about the conversion framework is that — over time — you start to understand and appreciate the 3 departments (marketing, product/tech, and operations) much more and especially their dependencies (and consequences of one change on the other).

So the best part of the FALCON Conversion model is that it is not a prescriptive model but a model that is focusing on outcomes. So action (and test) on every insight and vice versa with a focus on continuous improvement.

So that’s our framework to scale an ecommerce business: by applying the conversion framework.

Have a different model in mind? Let’s connect and let me know your thoughts!

Avtar Singh & Alina Odintcova have contributed to this article.

This article first appeared in THE STARTUP – mediums largest entrepreneurship publication followed by +350K followers