What is Customer Analytics + Analysis – Behavioral Segmentation Model
Customer analytics enables retailers to better understand their audience by making visible consumer patterns. By breaking it down to different groups according to customer behavior or what is often referred to as behavioral segmentation retailers can better communicate with the customers.
Customer analytics greatly improves corporate performance for those who use it often, this was the takeaway from a survey carried out by McKinsey way back in 2013.
Today in 2020, in the midst of the COVD-19 pandemic, nowhere is this more evident than in the retail sector where customer analytics is routinely deployed on eCommerce platforms like Shopify for the purpose of better understanding customers and behavioral segmentation.
Huge changes in consumer behavior have caused chaos for retailers in recent months with drastic falls in some product categories and yet others have risen nicely. Having the data to hand is the essential first step to understanding behavioral change, but it is worthless if you don’t know what to do with it.
It is what is done with the data which separates the winners from losers.
Only those who can adapt to changing consumer behavior, made visible through customer analysis will survive. Moreover COVID-19 is an opportunity to displace the long term, sector leaders.
Table of Contents
What is Customer Analytics?
Customer analytics provides a means by which data can be collected on Customer behavior.
The interpretation of this data provides clear trends of behavior over time (a cluster analysis), these patterns of customer behavior can be leveraged to respond to changing consumer requirements and thereby assist to make better business decisions. The term predictive analytics should be used to the above.
Customer analytics and customer analysis enables behavioral segmentation into customer groups or personas based on past behavior, like previously purchased items or content interaction. The purpose of course is to enable targeting based on predicted future behavior.
Without proper interpretation your data is useless, or if improperly analyzed it is dangerous to your business potentially resulting in bad decisions.
Your analytics dashboard is where your decisions are informed. eCommerce analytics providers like Conversific have made it easy to interpret data, reducing errors in interpretation and all the while increasing conversion rates and sales.
What is Prescriptive Analytics
Prescriptive analytics is often referred to as the last frontier of analytics. It is based on predictive patterns of behavior, which often provides a clear path for improvement. It all starts with understanding your customers through data.
Prescriptive analytics goes beyond just predictive analytics into the realm of data interpretation using AI-based algorithms to prescribe a course of action, a recommendation, or in some cases an automated course of action.
What are the Best Shopify Analytics Tools?
The best Analytics tool to use with Shopify is one that is not limited to just Shopify’s analytics but uses Google Analytics as well. As a Shopify user, your data access is limited, for example KPI reporting and data access is limited according to the pricing plan you are on. Conversific combines GA data and that which is available on your Shopify plan to provide the data you need in a clear holistic dashboard.
Two sources of data make for more accurate reporting and provide redundancy for any downtime or bugs that might occur with either Shopify or Google Analytics while taking into consideration the differing forms of tracking. In addition, being less reliant on Shopify analytics data prevents you from being locked down to Shopify over concerns of data consistency. The use of GA also enables powerful custom reporting otherwise unavailable.
What is Customer Analysis
The goal of the customer analysis is to personalize your customers journey on your Shopify store, it answers the question of who your customers are from what they do answering the question what they are looking for, enabling you to give them what you think they want.
Customers that have similar profiles are grouped together to create customer profiles, these might also be referred to as a persona. Whatever the terminology used, it is essential to build your marketing strategy, specifically your content marketing strategy, sales strategy, and product development strategy around personas and a customer journey for each persona.
The problem with analytics is there is a certain amount of guess work, – filling in the blanks but then a customer analysis should not just be based upon customer analytics, but also customer feedback, and customer surveys, and last but not least, focus groups. Today, all of these can be carried out remotely, even focus groups.
What is a Survey – Survey Definition
Consumer surveys are typically cross-sectional studies, quantitative research differing from focus groups in that the outcome can be conclusive (depending upon the questions asked). Historically, customer surveys tend to be long-winded, tedious to complete. These tend to be delivery by:
- By mail
- By email
- By website, – embedded HTML or popup
Customer Analysis is increasingly important because of the ever-increasing trend towards customer personalization of the customer experience through behavioral segmentation. Every aspect of the consumer journey can now be configured according to their interest. From website experience to customer feedback, the customer journey is enabling manufactures to be Agile, detect changing customer requirements, and create product variants to accommodate those needs.
Customer surveys are an important part of this customer analysis enabling highly focused questioning of their wants and needs, not obtainable from customer analytics. These can carried out online via a simple online survey tool.
There are many advantages to an online survey tool.
- Survey templates
- Drag and drop popup / embedded survey builders
- Easy to brand
- Accuracy, online surveys have a low margin of error
- Quick and easy
- Break survey into sections
- Increased participation
- Low cost
What are the Best Customer Survey Tools for Shopify Plus?
Simple Survey ToolsSegmentation criteria includes There are many tools designed for the purpose of surveys and collecting customer feedback. It really depends on your needs as to which tool is best. Note that features are limited according to pricing plans. Your selection should be greatly influenced by the ecosystem of tools you are using and the integrations available.
- Survey Sparrow
- Survey Monkey
- LimeSurvey (great if you need a self-hosted option)
- Survey Planet
- Survey Gizmo
- Survey logic
- Export of data
- White labeling (own logo)
- Question type range (dropdown selection, star rankings etc).
- Integrations available (3rd party tools like Salesforce or MailChimp)
Customer Research AnalysisIt is often better to opt for a niche best in class tool when it comes to eCommerce, for example, a tool designed for use with your eCommerce platform (Shopify or WooCommerce for example), with features that enable you to carry out consumer research analysis on your own website. Why? Ultimately all forms of communication drive traffic to the business website, so why use any other channel for surveys? If this is your use case then a Conversion rate optimization tool would be better suited for your needs rather than the tools listed above. For example, OptiMonk enables the collection of data of individuals when they come to your website, based on the data you request and they supply (custom data fields), you can target those same individuals and then trigger a survey based on different criteria (data held by you about them). You can even combine and target individuals with multiple custom fields along with any other demographic data held. It enables you to retarget those same individuals using that data. This makes it useful and cost effective for Consumer research analysis.
For Consumer research analysis segmentation criteria include
- Value of predicted group income is greater than costs
- Personas can be clearly defined, – distinguishable
- Fits within the core message/product range (if not consider creating a new store) and therefore keeps your marketing messages on target.
For example alongside the conversion rate optimization (CRO features) of OptiMonk, there is an easy to use drag and drop survey features and templates alongside other customer analysis features such as customer sentiment tools (NPS Nanobar + customized scales) and multistep feedback/survey tools. The true value here is that you can integrate these surveys/sentiment features within the eCommerce customer journey and conversion funnel thus enabling you to trigger them at highly specific points, for example after purchase making sure you get the data you need.
The take away from this tools section is that the scope of tools is constantly changing and so an annual review of tools is needed to eliminate duplication of features where possible for cost savings and to stay up to date with innovative new options for your industry.
What is a Focus Group
A focus group is designed to gain understanding customers’ motivations, the reasoning behind decisions. This includes the subject’s emotion which is invaluable when you consider the importance of emotion in the decision-making process. This is particularly true for purchasing decisions and more generally in eCommerce.
OptiMonk provides the means to trigger a survey at exactly the moment needed so that you can then try to determine what is driving their purchasing behavior through descriptive answers, however, what it does not do is supply the necessary environment necessary to be classed as a focus group.
Typically focus groups are carried out in interactive groups enabling the subject to elaborate on ’why’ they think in the way they do. Responses feed off each other and the questioner needs to adapt in realtime to the interaction, adjusting questions to take into consideration the previous answers.
However even this can now be done remotely.
Gone are the days when costly focus groups need to be carried out in person, – in RL. Today the technology is now accessible to everyone to carry out focus groups remotely.
What is a Customer Customer Segmentation Model - Behavioral Segmentation ?
Personalization through customer segmentation improves Shopify performance. Even Shopify Plus custom themes top out around 4-5% conversion rates, everything else requires a greater level of personalization using customer segmentation to supply customers what they need, when they need it. It improves conversion rates on both micro conversions and macro conversions (sales). There are many models and variations of customer segmentation models. One customer segmentation model frequently cited is fairly old now, published in 2009 but are still used as a base for modern ones.
An eCommerce segmentation model includes factors such as:-
- Demographic data including, gender, age and
- Traffic source + returning customer?
- Psychographic data (custom fields data collection), preferred product categories, shopping cart contents, visitor frequency.
- Shopping cart value
No matter where your data is secured your business liable for its storage and use. Whether you decide to keep the data on-premise or choose to entrust the security expertise of 3rd party SaaS tools, there are risks involved.
Here is how Conversific Helps to Identify Unknowns and define Segments.
Customer analysis defines how you place your store within the marketplace. From it you can determine your customer personas and design customer segmentation strategy, and base the consumer journey upon it. Therefore, your analytics data is essential because it is the principal means of understanding your customers in 2020.
3rd party Shopify analytics providers are adapting to the needs of Shopify etailers, providing key KPI reports, bypassing the restriction applied by Shopify to its reports (limited by pricing plan).
Conversific is a Shopify Google Analytics tool, it enables the interpretation of Google Analytics, eCommerce data in combination with Shopify data. Clear, useful dashboards inform vital decisions bypassing Shopify price plans in many cases. This provides a vital alternative for professional reports and for those times when profits do not warrant the scaling up of Shopify to higher, more expensive plans. Another interesting case is where a business has multiple Shopify stores.
Customer analysis is more than just the interpretation of analytics data, it should use other data too, possibly from many other silos, such as data from survey tools, social analytics, advertising platform data, etc. Each and every one of these tools and tool types have their own complex pricing plans and data export restrictions.
Deciding on a path forward requires reflection on existing tool use and the consideration of alternatives, – reviewed annually since tool features change adapting to customer needs. Opt for a use case-specific tool, for example an eCommerce optimization tool rather than a marketing automation tool that is designed to be all things to all marketers.
Look for best in class features that enable you to not only carry out customer analysis, via analytics but also enable you to segment and target your Shopify audiences effectively on your own website (visitors tend to accept tracking as inevitable when they visit websites). Features like geotargeting, AB testing, dynamic text replacement, and eCommerce specific features such as a product recommendation engine to name but a few. Target users by Shopify cart contents by item or by value and upsell/cross-sell or offer discount coupons to drive home those sales.
Your selection should consider the integration options available. Finding the right balance between flexibility and expertise in use is always tough.
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