Proper customer segmentation is important because it allows businesses to focus their marketing efforts on specific target markets more likely to purchase their products or services. As there is always a scenario where you’ll find a group of a target audience that you have been not able to cater to for your products/services. So, segmenting your customers is a vital process.

From effectively targeting consumers to creating a personalized customer experience, customer segmentation is essential for any business looking to succeed in today’s highly competitive marketplace.

But, what is Customer Segmentation?

Customer segmentation is the process of subdividing your target audience into different segments depending on similar variables and characteristics of customer profiles.

These variables & characteristics can be of distinct categories like demographics, income, psychographics, behavioral etc. to determine the segment in which one particular customer would fit.

And, customer segmentation also helps organizations to create an ideal ‘buyer persona’. This will guide the businesses to market & sell the products/services with a personalized pitch, generating a higher rate of success.

Issues in Customer Segmentation:

Here are some of the issues that make customer segmentation difficult for any new business:

• Lack of Data & Right Data Collection Process: For an effective customer segmentation model, it is crucial to have access to a vast amount of data which includes customer demographics, purchase behavior, and other transactional data. Without this data, it isn’t easy to create meaningful customer segments. Moreover, it is vital to have a proper data collection process in place. As it makes the segmentation easier and also helps in the integration of the data seamlessly into different required channels.
• Difficulty Identifying Relevant Variables: Even if you have data, defining and deciding which variables to use for segmenting customers can be challenging. You need to identify variables relevant to the customer and their behavior.
• Choosing the Right Segmentation Strategy: Many different segmentation strategies can be used, such as demographic, psychographic, and behavioral segmentation. Choosing the right strategy can be challenging and requires careful consideration of the customer data and objectives.
• Unreliable Data: Inaccurate or unreliable data can result in ineffective customer segmentation. It is important to ensure that the data is accurate and up to date before segmenting customers.
• Keeping Segments Up to Date: As customer behavior and preferences change, the segments need to be updated to reflect those changes. This can be a difficult and time-consuming task.

Traditional Customer Segmentation Process

Traditionally, organizations would use a combination of demographic, psychographic, and behavioral data to segment their customers. Demographic data includes information such as age, gender, income, and education, while psychographic data focuses on the customer’s personality, values, and interests. Behavioral data, on the other hand, look at the customer’s purchasing habits and patterns, as well as their engagement with the brand.

Organizations would gather this data through customer surveys, focus groups, and transactional data from their sales and marketing systems. The data would then be analyzed to identify commonalities and trends among customer segments. Based on these insights, organizations would create customer segments and develop targeted marketing strategies for each segment.

Drawbacks of Traditional Customer Segmentation

Despite being an effective way of understanding and engaging with customers, traditional customer segmentation has its drawbacks. One of the biggest challenges is the lack of data. To accurately segment customers, organizations need to have access to a vast amount of data that includes both demographic and behavioral data. Without this data, it is difficult to create meaningful customer segments.

Another major issue with the traditional customer segmentation model is identifying relevant variables. Even if organizations have access to data, it can be complicated to decide which variables to use for segmenting customers. For accurate customer segmentation and customer behavior analysis, choosing the right variables is critical.

Additionally, traditional customer segmentation can be unreliable if the data is inaccurate or out-of-date. This can result in inaccurate customer segments and ultimately impact the effectiveness of marketing efforts. Keeping customer segments up-to-date can also be a hassle and exhausting task as customer behavior and preferences are constantly changing.

Despite its limitations, traditional customer segmentation has been the standard approach for organizations looking to understand and engage with their customers. However, with the rise of location data and intelligence, organizations now have a new tool at their disposal to segment their customers effectively.

New Approach (Location data and intelligence): How GeoIQ solves these issues?

The rise of big data and the availability of location data has made it possible to augment traditional customer segmentation methods with location intelligence. With GeoIQ, organizations can now analyze the impact of location on customer behavior and preferences, giving them a more complete picture of their customers. Using location data, businesses can identify the relationship between a customer’s location and purchasing behavior. This enables them to make more informed decisions about which products or services to offer and how to market them.

As discussed, the challenges of the traditional customer segmentation model are the lack of data and difficulty identifying relevant variables. GeoIQ solves these problems by providing businesses with access to a wealth of location data, including demographic, psychographic, and behavioral attributes.

This data is combined with advanced analytics tools to help organizations identify the variables that are most relevant to their customers and their specific locations.
A good customer segmentation model requires accurate and up-to-date data. Using advanced real-time data management tools and processes, GeoIQ ensures businesses’ data is reliable.

Furthermore, GeoIQ regularly updates its data to ensure that its customers always have access to the latest information.

Finally, keeping customer segments up to date can be a complicated and time-consuming task. GeoIQ solves this problem by using machine learning algorithms to constantly monitor and update customer segments based on customer behavior and preferences changes. This ensures that businesses always have access to accurate and up-to-date customer segments.

The Impact of Location Intelligence on Customer Segmentation

A business’s success can be significantly impacted by the effectiveness of the customer segmentation model. As a result of customer segmentation, companies are 130% more likely to be able to identify their customers’ motivations and 60% more likely to understand their concerns and challenges, which directly translates to increased lead generation and revenue.

When you segment your customers via location data & intelligence, you can more effectively target your marketing and sales efforts, which can lead to increased revenue and growth. Additionally, segmentation can help you better understand your customers’ needs and how to best serve them.

Some of the major impacts of the customer segmentation model based on integrating location data & intelligence are –

1. Improved customer targeting: By using location data, a business can identify areas where their products or services are in high demand and target their marketing efforts to those locations. This can help them reach the right customers with the right message at the right time.
2. Increased efficiency: Location intelligence can help businesses optimize their operations and resources. For instance, A retail store might use location data to manage its inventory and ensure that the aptest products are in the right place. Enabling businesses to reduce operational costs and eliminating the time-consuming process of finding the best location.
3. Competitive advantage: By leveraging location data and intelligence, organizations can gain a competitive advantage over their competitors. For example, a retailer might use location data to open a store in a location where there is high demand but little competition. Thus, giving in-depth insights to make informed decisions and grow at scale.

In short, integrating location data & intelligence into the customer segmentation model effectively reduces the hassle of guesswork, allows for better targeting, improves the customer experience, increases efficiency, and provides a competitive advantage for businesses.

Use-cases

An online marketplace for pre-owned gadgets: Pre-owned smartphones and other goods like laptops, gaming consoles, smartwatches, cameras, etc. are simple and convenient to buy and sell online.

Challenge: To explore hyperlocal catchments with a high density of target audience. Identify look-alike areas to target their campaigns.

The brand could identify its major markets to have a high presence of local mobile resellers and retailers. They could identify a new sales channel, a B2B2C model wherein they could target the mobile and electronics resellers who in turn would target the end consumer. This model helped them spike their sales numbers radically.

By exploring users’ behavior and preferences to hyper-target them. Targeting users through location data leads to better customer segmentation and personalized user experience. The presence of brands, access to branded apparel shops, location of the users, etc. can help Cashify streamline the sales funnel by launching highly engaging, tailored campaigns across numerous platforms.
This helps the company to boost its overall conversions, as well as allows them to better understand its users and lessen the likelihood of funnel drop-offs.

A global healthcare company: To ensure that they have information to transmit that would be well-received by providers, patients, and payers equally, it is necessary to think about implementing bigger strategic adjustments. It needs to engage not only with the appropriate audiences but also more effectively than ever. The company’s customer segmentation strategy was designed to help them identify and target the most profitable customer segments while tailoring their products and services to meet the specific needs and preferences of each segment from behavioral, and demographic to geographic insights. By focusing on the needs and preferences of their target customers, they could develop effective marketing campaigns, build strong customer relationships, and ultimately drive growth and profitability for their business.

The brand was initially targeting mid-aged women for their medication for menstrual pain and cramp relief and the target areas were residential apartment complexes, gated communities, the absence of commercial catchments, etc. GeoIQ’s ML model identified a new target segment altogether that was, school-going girls and areas with a high presence of schools to boost their sales. The sales numbers of the high potential low sales stores were predicted to drastically increase once the activations were placed.

A savings wallet financial services company: By leveraging user data and feedback, fintech companies can gain a deeper understanding of their customers and create more effective and personalized marketing campaigns that drive user engagement and loyalty.

User data such as transaction history, and identifying their location such as urban, rural, commercial area, residential area, affluence, etc. was cumulated to identify spending patterns and offer personalized recommendations for financial products and services that align with the user’s financial goals. With the help of demographic information from user registrations to tailor their messaging and promotions to specific age groups, income brackets, or geographic locations. Our model identified spending patterns and offered personalized recommendations for financial products and services that align with the user’s financial goals.

The savings wallet provider used our models to create geo-identities of user’s basis savings brackets and targeted different communications for each of these segments.

Conclusion

Customer segmentation is a critical part of any successful business strategy. With GeoIQ, businesses can eradicate traditional customer segmentation challenges to engage with their customers and drive sales through the use of location data and intelligence. Whether you’re a small business just starting out or a large enterprise looking to expand, GeoIQ can guide you to achieve your goals and reach your full potential.

For more information on our products and services, you can visit www.geoiq.io or get in touch with us at hello@geoiq.io.