Segmentation Analysis

Data Segmentation: 5 Easy Steps to Organize Data

Collecting data on customer background and their buying habits can help you succeed in business. When you know your customers, you can model your products and services to fit what they need. It can also help you develop customized promotional messages according to your target market.

Data collection, however, can be a painstaking process. Essentially, you are dealing with a vast market with different backgrounds, motivations, and behavior. With so much information to collect, big data can be overwhelming. When mishandled, instead of knowing more about your market, you could end up confused.

To ensure that you are getting the most out of the data you collected, you need to deal with all the information in an organized fashion. This is where data segmentation comes in.

What is Data Segmentation?

Data segmentation is the process of categorizing the data you collected based on their nature. When you segment your data accordingly, you can see how disparate your customers are. When you have this data, you can analyze your customers more accurately. Consequently, you can extrapolate more reliable conclusions from having your data organized in this fashion. When done right, it can help you improve sales and marketing productivity.

Data Segmentation Process

1. Set a goal for your data collection

Segmenting data can take time. To shorten the process, you need to set goals. First, you have to identify why you are doing it in the first place. Being clear about your purpose can limit the information you need to collect and go through, processing only the most useful data for you. For example, if you are interested in learning your customers’ demographic profiles, you want to gather information about their age, gender, education, work, and family income, among others.

If you are planning to launch a new product or improve an existing one, you need to collect data on the benefits your market might be looking for. If you are curious about where your products are most marketable, you can focus on gathering geographical data.

This grouping of customers based on specific categories is called market segmentation. It’s a way of grouping customers based on different criteria. Other criteria include the personal habits of customers when buying or their capacity or willingness to pay.

When you are clear about what you want to know about your customers, you are more likely to gather the data that will help you better understand them, instead of collating irrelevant information that will only be confusing and unhelpful.

2. Come up with hypotheses

Data collection is research. Making reasonable assumptions based on the current observations, you have can guide you towards arriving at an accurate answer. If you don’t know what you will possibly find in your research, the process can lead you astray.

For instance, if you are in the business of beauty products and want to know your most profitable customers’ age group, your hypothesis can be that they are women from 18 to 35 years old based on past observation. This assumption can narrow and specify your data collection process, leading to a more accurate conclusion.

However, this is not foolproof. It’s possible that the hypotheses you set can be too limiting that you arrive at obscured data instead. To avoid this, you can broaden the range of research from your original premise to other possibilities.

After you identify how women aged 18-35 years old respond to your products, you can compare your finding to that of the behavior of women outside such age range.

By testing your hypothesis through existing variables, you can align your business view to how your customers receive it. Reconciling the possible differences can help you improve your products and customer satisfaction.

3. Select a data-collection tool

Once you have identified what data you need and what you expect to find, the next step is choosing the most effective data-collection tool. Your options range from doing a survey, sending questionnaires, conducting interviews, observing purchasing habits, and setting up focus groups.

Technology can carry this out with a broader reach and efficiency. Social media and analytics software have become effective ways to know and understand your market. Facebook and Twitter are common platforms to reach out to your audience. You can engage with them through surveys and interviews.

Putting up a website can give you more immediate and personal knowledge of customer behavior. Analytics tools, such as Google Analytics, can detect how long a particular user views your products and how quickly they switch from one web page to the next. This is a more reliable source of information as customers’ behaviors say more about product engagement than their verbal or written response through interviews and surveys.

There is no overemphasizing the importance of selecting and utilizing a data collection method. Its level of accuracy and efficiency will define how reliable your data is and, ultimately, the quality of results you draw from them.

4. Analyzing the relevant data

This is the heart of data segmentation. After the tedious process of collecting data, you can now categorize it based on your purpose and hypotheses.

To maximize what you’ve collected, you need to focus on what you want to know. Analyze data that is most reflective of your market and remove the insignificant indicators. For example, if you need to understand your heavy-use customers’ behavior, you need to disregard data from new or light-use customers. If you want to know how a particular gender responds to your products, you need to analyze that gender’s behavior alone. If you want to learn whether this mirrors a trend in other genders, then you can make the necessary comparisons.

You should also consider your hypotheses as mere guides in interpreting the data. After all, they are assumptions based on past observations and may no longer be reflective of current trends. Take them into account but be reminded that they are not central to the evaluation process.

It’s also vital that you carry out analyses in teams. With big data, it is easy to miss something that could be the defining factor of the entire research. When you have enough people evaluating plenty of raw information, you can reduce the risk of misinterpretations.

5. Acting on results to finalize data segmentation

Once you have analyzed and interpreted the data, you will now have identified whether your hypotheses and your research match. From the conclusion, you can now design products and promotional messages that are more likely to get a more robust response from your existing and future markets.

Through data segmentation, you can see your customers not as one big group but as individuals. You improve the market knowledge you have that allows you to develop personalized products. You can also identify the type of communication your target market is more likely to respond to. As a result of this level of understanding about your market, you end up customizing your messaging and devising customer-friendly marketing strategies.

All this can translate to efficient use of resources, a more substantial market presence, and even increased sales.

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