Data Segmentation – Key to Generating Value to Your Business
Published on: December 10, 2021 Updated on: June 26, 2024 969 Views
- Web Analytics
8 min read
Client satisfaction is the key responsibility of any business. More than anything, creating personalized products and services that meet consumers’ demands is essential. This is why data segmentation is considered as an effective strategy, as it depends on the buyer’s persona and collected data to create customized messages.
According to a HubSpot report, segmenting data and using marketing personas helps businesses create 2-5 times more effective websites.
Data segmentation aims at dividing the audience into distinguishable groups and sending them with tailored and more targeted content.
The competitive marketing environment demands knowing who you are trying to reach or talking to so that your message falls in the right place and generates the desired conversions. With data segmentation, you can create tailored messages for your targeted audience for them to convert. It can be accomplished by retargeting content.
In this article, we will cover data segmentation and how it adds value to your business.
What is Data Segmentation?
Data segmentation is a smartly initiated process of using data resourcefully for marketing means and business operations. The unstructured and bulk data is consumed with the help of data segmentation techniques, where it is organized strategically and divided into defined categories based on people’ interests, characteristics, and more.
What Are the Benefits of Data Segmentation?
- Targeting right audience
- Lead generation
- Improving customer engagement
- Boosting brand loyalty
- Optimizing cost-efficiency
- Developing niche products
- Enhancing outreach success rate
- Implementing data-driven marketing
How Does Data Segmentation Add Value to a Business?
Attracts Audience Through Content
One way to swoop in the benefits of data segmentation is through content creation. Even the renowned and most popular brands create content to attract their audience. The best solution here is to come out with relevant topics tailored in the interest of your prospects.
Whether it is an ecommerce store or a SaaS business, each company has different potential buyers. So, you will always have a varied group of people interested in your products and services. If you can identify them, you are all set to create something better and unique for them.
But before you proceed, remember the three W’s – who, why, and what.
WHO are your content readers?
WHY should they care about your content?
WHAT value can they generate from your content?
With the right tools, like Google Analytics, you can find out the answer to your WHO. Once you have defined your target audience, you can scrutinize why they should care about your content. And then create content that adds value to them.
Generates Revenue
Segmentation is all about segregating the customer data and using it in a way to benefit you. Evaluating customer lifetime value, average order value, and purchases, you can categorize customers based on acquisition costs and revenue generated. The analysis can help in refining your marketing strategy and boosting revenue.
To generate revenue, you need to provide the best to your customers, and for that identifying them is critical. Google Analytics, SEMrush, and HubSpot are some examples to get you started.
The trick to finding the best customers is by checking their lifetime value, customers with the highest are your targeted prospects. Once you have the details of the right customers, you can improve your efforts in attracting more of them to boost more revenue per customer.
Apart from this, you need to be more vigilant if you want your targeted campaigns to work, and it can be done by finding the right acquisition channels.
Observing, testing, and identifying leverages your marketing efforts. You can certainly check which efforts go your way and which doesn’t.
Furthermore, with the right information, you can increase revenue, prioritizing resources that already drive more revenue and reducing expenditure on the resources that don't perform well.
Minimizes Churn Rate
The goals of companies have been modified. Instead of only focusing on customer acquisition, they are investing time and resources on customer retention.
One of the biggest losses a company can observe is the increase in customer churn rate. There can be plenty of reasons a customer can leave a business and data segmentation helps in attrition.
But before you start strategizing customer loss, you need to find who your lost customer is, and it can be done by analyzing their purchase cycle. For this, you need to have a defined threshold or a time frame that is the maximum number of days for which a particular customer is anticipated to make a purchase. If the number exceeds, your customer has churned out.
Data segmentation improves retention by monitoring customers’ journey, identifying the risk of churn, and creating specialized context to put them into retention campaigns.
For example, if you have a threshold of three months i.e. 90 days, and all customers who have not made any purchase in the past 60 days should be added to the retention campaign. Then, present them with a smart and personalized offer to prevent them from walking out.
Top Challenges in Data Segmentation
Delivering Insights Timely
Everyone wants to go big, but sometimes it can be challenging. This means, segmenting small chunks of data is easy and straightforward. But in the case of a massive amount of customer data, segmenting can be a lengthy process, which might cause a delay in delivering the segmented data to the sales team for the next operations.
However, we have a simple solution for this. By knowing why and who you are targeting, you can concentrate on the customer segment and use it instantaneously, helping your sales team with the highly-targeted list to proceed. Moreover, your marketing team can refine the targeting list and build campaigns across this.
Gathering Sufficient Data
One of the tricky things is knowing when the data is sufficient. Sometimes, companies don’t have complete information; some marketers have phone numbers, while some only have email IDs. Though you can take email address or phone number as a common factor, people use multiple email IDs or phone numbers, which can result in redundancy.
In order to fix this situation, data enriching comes handy. It enhances your customer data by affixing incomplete details, which is usually gathered from external sources.
Now that you have a clear understanding of what data segmentation is and how it can benefit in attracting the masses, you need to start strategizing your marketing campaigns around it.
5 Tips to Improve Data Segmentation
1. Data Enrichment
Companies have significantly increased their visibility and now can gather and segment data to build decisions based on customer behavior. However, data segmentation is incomplete without data enrichment. Each segment created requires reliable data and without enriching it cannot be accomplished. Therefore, an updated database to stay relevant should be your top priority.
2. Omnichannel Strategy
Tracking customers’ journey is getting a lot more complex (as they use multiple devices) with oodles of sales channels. Let’s talk more about this with an example. A customer checks a product online, goes to another store for more seamless choices, but ends up buying it from a retail store. Well, situations like this will not help in understanding your customer behavior.
Buying a product/service is a whole journey, from checking a product to putting it in the cart, and then finally purchasing it. Customer’s journey switches from one platform to another. So, if you are focusing on a single channel or platform it will not generate the desired results.
For example, if your customers want to engage with you on Instagram, but you are not only present on Facebook, then they might be disappointed, which can lower down your engagement rate and can possibly lead them to churn out. Omnichannel strategies aid in tracking their customer’s journey.
3. Segmentation Done Right
Using the same data segmentation criteria every time can severely impact your business. For every business data, segmentation criteria should be different. When you decide to jump to customer data segmentation, you need to be clear with the purpose and the consumers you are targeting.
4. Real-Time Data Segmentation
Data segmentation tools like Google Analytics can help you to track the performance and journey of your customers. With this data, you can create customized content to target your audience. Segmenting data when combined with automation and predictive analysis can help in reaching the right set of audiences with the right offers at the right time.
5. Data Segmentation Based on Customers’ Lifetime Value
You can segment data based on your customer’s journey, their purchase, and interests. Remember, when it comes to customers, only one strategy can result in missing leads. Thus, you need to prioritize your customers based on their lifetime value.
Takeaway
Today, data segmentation has become the need of every business to effectively communicate with their target audience and customers. If companies want to reach the right set of audiences, they should never miss out on this. Segmentation of data is a key strategic objective to create relevant, customized, and effective marketing initiatives. The aim is to create campaigns that with specific groups to attract an audience, convert potential customers, and generate revenue. Use data segmentation to add value to your business and consumer data.
Frequently Asked Questions
Data segmentation is important for businesses because it allows them to target specific customer segments with personalized marketing messages, products, and services, increasing relevance and effectiveness.
Data segmentation generates value for businesses by enabling them to tailor offerings to the unique needs and preferences of different customer segments, leading to increased customer satisfaction, loyalty, and revenue.
Businesses can segment their data effectively by identifying relevant criteria for segmentation, such as demographics, behavior, or purchase history, using data analysis tools and techniques to identify patterns and segments, and implementing targeted marketing strategies accordingly.
Some challenges businesses might face when implementing data segmentation include data quality issues, privacy concerns, complexity of analysis, and the need for integration across different data sources and systems.