When an online retail channel is underperforming, the problem is rarely contained neatly within the website.
What appears to be an eCommerce/digital problem can originate in the customer experience, commercial strategy, operations, employee accessibility, and technologies.
The digital/eCommerce is the most complex business channel in history for a reason. There are so many things that can go wrong, and one weakness can trigger a domino effect across the entire digital channel.
As a result, the process of identifying the causes is as robust as the digital channel itself.
This article takes you through this process to help you understand the layers of scrutiny needed to identify digital channel performance issues and the solutions needed to course correct it.
This will also help explain why your past efforts in fixing this channel have also been unsuccessful.
This methodology has come from 25 years of "doing" and working alongside the top eCommerce practitioners in the world.
Step 1: Identify "what is happening"
The investigation begins with quantitative data, this is the behavioural data that defines consumer behaviours. This data explains what consumers are doing when they are engaging with your channel.
Humans vote with their actions. They can tell you they like you, but the key insight is seeing what they do when they have intent to buy.
- Conversion rates may have fallen
- Customers may be abandoning at a particular point
- Mobile performance is different from desktop
- A product category may attract significant traffic but produce disappointing sales
- Repeat purchase behaviour may have changed
These behavioral signals establish trends that require investigation.
This is "Step 1" because this sets the tone for Step 2.
Step 2: Identify "why its happening"
Only once the behavioural trends identify the issues can step 2 commence. These actions happened for a reason. These actions from humans have been activated as a result of something you can control.
We know this because people come to you with a purpose. They want buy something. This means if they come to you with that purpose and they do not achieve that purpose you have blocked them in some way.
The behavioural data in step 1 explains what the blockers look like. For example it could be checkout, mobile journeys, or product detail pages.
But these are merely visual symbols of deeper root causes. This steers us but does not give us any answers.
This is the power of Step 2, we need to understand why the checkout is producing huge bailouts (for example).
Car Crash Analogy:
Forensic science has used the same investigative logic for decades.
When a serious car crash is investigated, establishing what happened is only the beginning. Investigators then need to understand why it happened before the root cause can be diagnosed and changes made to prevent it happening again.
The process is:
What happened → Why it happened → Root cause → Solution.
Fixing an underperforming digital channel requires the same investigative discipline.
This forensic science analogy is explored in more detail here →
Customer Centric Data = "Why":
The digital channel produces a high volume of rich customer centric data also known as qualitative data.
This is the type of data that tells the business exactly what pain the digital channel is causing people when they are trying to engage and purchase.
And because step 1 clarifies what is happening, this data is scrutinised around the behavioural trends.
Examples of this type of data is...
- Incoming emails and phone calls
- Live chat logs
- Social interactions
- Interviews with frontline staff
Once we understand what is happening and why its happening can we then proceed to step 3.
Pulling Together the Silos:
The data needed to understand the problem is rarely sitting together in one convenient bucket.
There is literally a hunting and gathering process required to find it across the business and pull it together.
Knowing where to look, what evidence matters, and how to connect it is another layer of expertise required to make this methodology work.
Step 3: Defining the Real Issues - the Diagnosis
Two people can be given exactly the same quantitative and qualitative data sets and reach very different conclusions.
The difference is the professional lens through which they interpret it.
After more than 25 years working across eCommerce, retail, business strategy and customer experience, there are ways to see relationships between customer behaviour, commercial performance, organisational capability, technology and this data.
That experience creates pattern recognition.
For example, what appears to be a conversion problem may have started much earlier in the customer journey.
This is where the data is pulled together and synthesised.
This synthesis cannot be taught. It is this valuable culmination of 25 years of interpreting data and making business centric change, and living the results that has created this interpretation expertise.
Step 4: Solution Creation - Defining the Change Needed
Finding the real problem still does not solve it. A solution needs to be created to precisely resolve the problems.
Having a background in customer experience design is a crucial skill set which allows this process to move from interpreting the problem to designing the solution.
This then becomes the map for technical teams to follow. This is the "secret sauce" and is how the dots are connected from data analysis to creating business value.
Conclusion:
Put simply the above process can be summarised as...
- The data creates the insights
- The insights drive the intreptation of what's wrong (defining the issues)
- A clear plan needs to be created that resolves the issues
- The plan is then tightly followed by all necessary teams
The digital eCommerce channel can feel like one big "car crash" that produces chaos, confusion, and anxiety.
However, with the right intervention, and the right subject matter expert, anxiety can be managed, the reason for the accident can be identified, and most importantly, change can be made to ensure it does not happen again.
About Greg Randall
Greg Randall is an eCommerce consultant and the founder of Comma Consulting. He has spent more than 25 years working with retailers and B2B's, helping them understand what is getting in the way of better digital performance.
His work combines eCommerce strategy, customer experience design, data and commercial pattern recognition to identify the issues that matter and what businesses should do about them.
This article was as tagged as Data Driven Decision Making , Digital Strategy , Digital Transformation