Product category analysis is a catch-all term, referring to any analysis of product categories that you carry out in order to understand what drives purchases. Starting with an overview of product categories, you parse through the data in order to glean more insight using techniques such as product development analysis and operations analysis, alongside competitor analysis and customer experience analysis.
Product category analysis isn’t a simple thing that just anyone can do, as it requires careful interpretation of the data and even data cleaning in order to get the most relevant results. The analysis must be automated by a computer due to the sheer volume of data.
Why You Should Use Product Category Analysis
Product category analysis can give you deep insights into how your products are faring in the current market, from the individual level all the way up to the category level. It condenses high volumes of data down into easy to digest forms for use, meaning you’ll be able to tell what’s happening at just a glance.
The analysis brings insight on various factors, and you can focus on one particular area that you think needs improving to gather, say, a product category attractiveness analysis. With the reports such an analysis produces you can easily compare your brand to your competitors, spot areas that could be improved and also identify your strongest products.
Product category analysis can answer key questions you have about the state of your business, such as:
- Who is/are my main competitor(s)?
This one might seem obvious but there are always those that you can miss.
- What products do my competitors sell?
Following on from the above, you can compare your products to theirs and see what areas they outrank you in and need to look to improve.
- What is the range of products offered within the category?
Given a certain category, are you a standout or simply one among many? Is there a niche or a gap that you could potentially fill?
- What do your customers think about you?
Customer experience and subsequent opinion drives returning customers and is a big factor in new sales. If you’re not getting the reach you want on a product, you need to invest more in advertisement.
What Are The Stages of Product Category Analysis?
Product category analysis is a step-by-step process, one in which you should complete each step as thoroughly as you can before moving on to the next. What you need to do at the beginning is simple — define your category. Some categories are subdivisions of others, resembling a tree structure or expanding flow chart.
Defining Data Requirements
Category analysis begins with data, and the more specific your data the more specific the results. What data you use is up to you and your goals, do you want to analyze on a monthly basis? Quarterly? In a general sense you can define your data requirements by asking yourself the following questions:
- What sources will you use, internal or external to your business?
- What time period are you looking at?
- How often do you want to collect data during that time period?
- What other brands are you looking at for comparison?
- What information do you want to see in the report?
While the first four are easy to decide, the last question might be a bit tricky if you’re first starting out. Beginning with general analysis and moving on to more specific trends can help if you’re not sure where your problems lie.
Collecting Your Data
Once you’ve defined what data you’re looking at, the next step is to collect it. Where this data comes from will vary depending on what platforms you use to collect it, e.g. social media, emails, website reviews etc. Any data you have stored can be used at this point.
You can also use website scraping tools to collect the useful information from other online sources such as forums or open databases, however your tool needs to be aware of sentiment analysis in order to properly interpret the data.
Processing the Data
Any data you gather is going to be disorganized at first, meaning without any standardized format. Your next step is to convert the data into a singular format that can be easily read, grouping the data such that information on specific products is together and so on.
Topics and sub-topics can be used here, with some subcategory reviews having some relevance to the parent category as a whole and vice-versa.
Cleaning the Data
When you obtain raw data, it’s not going to be what is referred to as “clean”. Essentially, you’re going to have incorrect formats, duplicates, errors, white spaces and such that will mess with your analysis and leave you with incorrect analysis. There’s also the factor of irrelevant information, in this case meaning information not related to what you want to see in the report, which should also be removed.
Data cleaning should always be performed before any analysis is done.
Once your data is cleaned, you’re ready to analyze it. This is done through various mathematical models and formulae, also known as algorithms. Which algorithm you use is entirely up to you, but there are a few common ones that are aimed at customer satisfaction. These include:
A prioritization algorithm that splits factors based on their desirability, with must-have, should-have, could-have and won’t-have categories.
An algorithm that splits factors into five “drivers”, from those that are taken for granted to those that consumers are completely indifferent on.
- Eisenhower Matrix
Another prioritization algorithm that sorts factors into urgent/not urgent and important/not important categories, allowing you to focus on the most time-sensitive issues.
Compiling Your Report
The final stage is converting the output into a readable form, usually into a report with graphs and charts for ease of reading. Spreadsheets and presentations are also widely used. The key aim of the report is to present category drivers.
Category drivers are the factors that help you understand what would cause a customer to use your product and what barriers exist that might prevent them from doing so. The ultimate goal of this analysis is, after all, to understand how to boost your sales. Category trends and insights based on them can also be found.
Sentimate Case Study: Drones
With our product insights engine Sentimate, you can use our product and category analysis tools to gain great insight into whatever category you wish. There’s no need to collect data, sort it, analyze it etc., we’ve done it all for you and have it ready to present in an easy to read format.
With that in mind, let’s look at a fun and interesting category, drones.
Sentimate lets you see the top products in a category and any new launches that have recently been released, as well as rising stars that have had a high increase in customer sentiment.
There’s also our competitive landscape tool, which lets you analyze either the top ten products or top ten brands within a category in any given month, comparing them on a chart of customer sentiment vs verified review volume. Using this, you can the category leaders and have links right to their product pages for further, individualized analysis.
The above is real data taken from our product insights engine, showing the top ten products in the Drones category for April 2022.
Looking at the chart on the right hand side, you can clearly see that the DJI Mini 2 Fly More Quadcopter is a leader in both review volume and consumer sentiment, indicating that it is both a top-seller and a high quality product.
Over on the left hand side, you can see the Maetot 1080P HD Camera Quadcopter, which while not having as great a number of reviews has a higher overall customer sentiment. This can be an indicator of a more specialized, high quality product, that while overall makes less sales will make up for it by having a higher price tag.
Using the individual product analysis tools you can track backwards across time, seeing where products stand on an individual level as well as how they have improved or not instanding over time for a more detailed analysis. You can track a product’s SWOT, compare it to others in its category and even see the top drivers and star ratings analysis.
There’s also the product map, offering a comparison of the individual product’s consumer sentiment vs the average of the category, topics of discussion and where the product fares in each of them. Our product topic map sets out these topics, both positive and negative, in an easy-to-read format that correlates the amount of chatter a particular topic has with the area it takes up on the map. Below you’ll find the product topic map for the DJI Mini 2 Fly More Quadcopter, arguably the number one product in the Drones category right now.
What Kind Of Data Can Be Used?
Data comes in all shapes and sizes, and the more channels you have available to gather said data the more informative it’s going to be. Some of the main sources of data include:
- Sales reports
- Customer emails
- Chatbot logs
- Customer surveys
- Social media posts
- Forum posts
While some might be more relevant than others, all data that you can gather will be useful providing it passes through the data cleaning process.
What Do You Get Out Of Product Category Analysis?
What information you get out of your product category analysis depends entirely on what you put in. That being said, there are a few key pieces of information that you will always get to some degree
- Category Trends
Category trends refers to any information on trends of customer behavior towards a certain category. Emerging trends that customers want to see, things that turn them away and add-on options that boost sales are all examples of such trends.
- Category Drivers
Category drivers are anything that prompts consumers to buy specific products when compared to alternatives. What these are will depend entirely on the category in question, but a good example would be the iPhone vs Android rivalry and which side a consumer stands on.
- Consumer Beliefs
Consumer beliefs can be tricky. Not only are they specific to an individual but they can vary wildly across different locations. That being said, generalizations can be useful, with one example being the public’s aversion to 5G towers and thus any 5G technology. Remember, it doesn’t have to be true for consumers to believe it, and that which is perceived to be true is often just as important or more so as what actually is.
- Brand Equity
Brand equity is a measure of your brand’s performance, specifically its performance in the public markets. It’s essentially the boost that a brand receives due to being well known, and therefore the worth of the brand name itself. A great example of this is Coca-Cola, who have a great brand equity when compared to a generic brand of the soft drinks industry. If you have high brand equity, your brand is trusted.
With the above in mind, there’s plenty of insights that we can gain from product category analysis, forming the basis for your strategies moving forwards. While these aren’t an exhaustive list, a few of them are:
- Product improvements
- Promotion/Advertisement strategies
- Positioning strategies
- Price adjustments
- Finding market gaps
- Learning which features of your products to emphasize
- Altering your business Model
- Finding new distribution channels
- Expanding production/processing
Product category analysis is a tricky and time-consuming thing to perform, with thousands of individual pieces of data needed in order to get a complete picture of any one product, never mind an entire product category.
Fortunately, Sentimate is here to help. Sign up for free today to access instant insights into products of all shapes and sizes.
Emily Louise Spencer is an in-house content writer at Revuze. She is a graduate of the University of York with a master’s degree in Chemistry. A published scientific author, she now works as a content writer and copy editor.