Customer Behavior

How to better understand your customers using behavior data and usage pattern

We have talked about the importance of understanding your customers earlier. It helps you on all fronts, whether it is in deciding the content on your website, the flow of said content, or how you should position different elements. The more your understanding of your customer improves, the better your marketing communication would get, resonating more and more with your target audience. And a combination of all this is an uptick on all fronts - more traffic, more conversions, more revenue.

Unfortunately, most businesses rely solely on the most basic metrics like pageviews, bounce rates, session duration, and conversion rates to understand their customers. The problem is, these basic metrics barely begin to scratch the surface, so a lot of what you would think as a customer behavior matrix ends up being inaccurate down the line. Why? Because while the basic metrics serve their roles, as far as making meaningful analysis is concerned, they represent not even half the picture, and the data is often out of meaningful context. As a result, any analysis made using the basic metrics often contains a fair bit of speculation and conjecture, with you making assumptions about what your customers need.

So let us look at how you should approach a better, more refined approach to understanding your customers using a combination of your web analytics data, user behavior data, and usage pattern.

No response is also a response

When someone fails to respond to a communication they were supposed to respond to, this is one of the things I say. No response says a lot as well. Sure, in communication between two parties, it leads to speculation and conjecture, but it does let you know that someone is dropping the ball somewhere.

In case of how a user navigates through your website and/or your product, a user not engaging with parts of your website/product is the equivalent of a no response. It means that either the user is not being exposed to these sections in the first place (easy to validate, and relatively easier to fix), or user is being exposed to these sections, but they just don’t interest him. The second scenario there is crucial and of import to the business.

It helps you understand what matters to your customer, and what parts of your messaging are just not resonating with your audience. The recommended course of action is to either fix the content of said sections to make them more aligned to your customers’ needs, pain points and expectations, or remove them altogether since they are not what your customer needs from your product.

No single data source, on its own, shows you the complete picture

Data is meaningful only when applied in the context of business growth, and when it comes to growth, you would often find yourself in need of analysing data from different sources and streams to get a better sense of things. No single data source on its own will be able to help you optimise your marketing strategy and/or performance.

Your business probably generates a ton of data for you. On traffic volumes, conversion rates, performance of different campaigns, traffic sources etc. While you can look at trend lines for any of these different data points, when it comes to developing a strategy for long-term growth, or optimising for short term performance enhancement, looking at any section is a piecemeal approach and doesn’t help you much.

Unless your analysis helps you understand why your conversion rates are going up or down, and what traffic sources are they going up and down for, or why customers are spending more and more time on certain segments of your website - you won’t be able to identify growth opportunities, or test their impact on your growth.

Formulating the right strategies start with asking a simple question - Why?

Why is my conversion rate going up this week. You start with that question and then you start working backwards from there, to the point where you can identify possible causes behind this upward trend. Possible causes that you can test out by consciously applying them on different sections of your product/website to replicate the growth elsewhere. If you are able to replicate the behavior, you were able to identify the right causes, and would now be able to drive growth across different marketing channels. You can not do an analysis that deep and expansive if you are just looking at the most basic data and traffic metrics.

This is true for most web analytics products and platforms. They will report the analytics data back to you, but for any analysis based on that data, you are own your own. Benne Analytics’ ever evolving and ever growing insights module does this analysis for you all the time. While your main dashboard primarily shows you basic trends and traffic metrics, the intent is to avoid overwhelming you with data overload. This is why primary growth indicators are shown on your dashboard, and any analysis on a wider and deeper dataset happens under the hood so that you get actionable intelligence based on that analysis, without overwhelming you with raw data.

Your web analytics data is not an insight in its own. It just helps you identify starting points for your analysis.

As we just saw, any meaningful analysis starts with one simple Why. But that why finds its origin in that data dashboard you see every day. Why am I getting more organic visitors? Why has the conversion rate suddenly improved? Why are we getting more signups these days?

Analytics data and traffic metrics are the starting point for understanding your customers. Do not make assumptions based on what you see on your dashboard, or blindly follow what your competitors have been doing. To optimise your effort, bandwidth and marketing spend, you need to optimise performance, and the best way to do that is to go down the rabbit holes of Whys.

Blend data with insights.

Data = what your customer is doing Insight = an understanding of why he is doing what he is

Growth focused platforms like Benne Analytics do most of the heavy lifting for you, and with a few simple setups you can receive much better and actionable insights focused on growing your business. But even if you are not using Benne Analytics or a similar tool, you should make it a point to undertake this exercise yourself to expedite growth.

Generating actionable customer understanding is all about following a result-oriented framework

The first step to doing this exercise is to gather and blend both quantitative and qualitative data from different sources, and coming up with a methodology to align it to your overall strategy.

There are three key components to this process:

#1. Performance analytics

Whether you are acquiring customers organically or via paid acquisition channels, you need to understand the efficacy of different platforms and channels. At the same time, you need to chart out the conversion rates of different stages of your customer journey, the overall conversion of your landing pages and your website, engagement rates of your emails and data on retaining customers.

You can make sure you have access to all of this data right in your Analytics dashboard by setting up tracking parameters correctly, a smart implementation of UTM parameters and setting up attribution models.

#2. Customer feedback

In addition to how your customers interact with your product, they also share their usage experience via feedbacks, support requests and their responses to surveys and questionnaires your may be sending from time to time. Mapping these interactions out vs prominent issues, keywords and pain points is imperative to understanding the most critical focus areas for your business.

In addition to relying on these modes of communication, it is strongly recommended to have one-on-one communication with at least a random selection of your customers from time to time to better understand how they are engaging with your product, and what are the reasons preventing them from taking certain actions you would have otherwise expected them to take.

#3. Constant analysis of performance

While #1 and #2 help you come up with hypothesis and possible growth routes, a constant analysis of performance of these hypotheses will help you optimise and fine tune them further making sure you are optimising for the best customer experience all the time, which ultimately translates to an improved performance and faster growth.

During these past 18 months, businesses have had to face the reality of importance and criticality of granular insights. With businesses coming to terms with unpredictable customer behavior, including drastic peaks and troughs in their traffic and conversion rates, unlocking the secrets to customer usage behavior became a more critical concern than it had ever been. Companies that were set up to generate blended customer insights were the ones that have been able to make better and bolder moves at commendable pace, while reducing their risk exposure at the same time.

In time, we will head back for normalcy. But the need to understand your customers better will not fade away. The need was always there. The chaos, uncertainty and unpredictability of the last eighteen months just stirred the pot enough to bring it to the surface.

What is the approach you follow to understand customer behavior better? What data sources you turn to? What analysis do you perform? I would love to know more about it. Hit me up.

That’s it for today, see you tomorrow.

Cheers

Abhishek

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