Data Segmentation: The Ultimate Guide

Targeting individuals who are interested or who have shown interest in your services would be more effective than targeting a broad audience of all age groups. This is where data segmentation proves to be helpful. 

Dividing your audience into distinct groups based on specific characteristics allows you to tailor your marketing efforts and meet the unique needs of each segment. This targeted approach connects businesses with their potential clients on a deeper level, increasing the likelihood of conversions. 

Now, the question is: Do you want your sales and marketing team to spend less time guessing, and more time closing deals? 

Data segmentation is vital for companies looking to improve sales and marketing productivity as it will help you improve your lead generation efforts, as well as gain key insights into existing customers. 

‍In this article, we’re going to show you: 

• How to use data segmentation best practices 
• How to beat common barriers to good segmentation 
• Real benefits of paying attention to how organized your data is 

What is Data Segmentation? 

Data segmentation is the process of how you divide and organize your data into defined groups, so you can sort through it and view it more easily. Segmented data will provide your team with clear, actionable information that can be used in your sales and marketing. 

We’ll focus on data segmentation for sales and marketing (sometimes referred to as sales segmentation). 

But, database segmentation isn’t only useful for sales and marketing. Armed with this knowledge, you can create targeted marketing campaigns that speak directly to the needs of each segment, increasing the effectiveness of your messaging and driving higher engagement. 

Additionally, you can apply data segmentation to your existing customer database to identify insights that can improve customer satisfaction, and grow revenue. 

Segmentation vs. Targeting 

We also need to be aware of the difference between segmentation and targeting. These two concepts are related but refer to different things. 

As we outlined above, segmentation involves dividing information into groups to enable you to use it more effectively. 

While “segmentation” and “targeting” are often used interchangeably. However, segmentation refers to the process of dividing your audience into distinct groups based on shared characteristics, such as industry, company size, or job title. Targeting, on the other hand, is the act of tailoring your marketing efforts to reach a specific segment or segments. 

For example, when creating a cold email campaign, you can segment your list by data such as job titles, company size, technographics, or other identifiable data. This will ensure you target each person on the list in an effective and personalized way. 

Your segmented data enables your targeting to be more accurate, and more effective. 

So, how does targeting tie into this? 

Targeting is the process your sales and marketing teams use to decide on the best strategies to promote your business to your ideal customers. 

This could mean identifying the best medium to contact your ideal customers (e.g. running ads on LinkedIn vs. on Twitter). 

Segmenting happens before targeting, and is the reason you can effectively target customers. 

Without a solid process to segment your data, your targeting will never be as accurate as you need it to be. Your sales team will struggle to see success with their cold emails and won’t be able to close many deals, as they’re talking to the wrong people. 

The Role of Data Segmentation for Personalized Targeting 

Data segmentation divides your audience into smaller and more manageable groups. This, in turn, allows you to create highly targeted messaging that speaks directly to the needs and pain points of each segment. This level of personalization not only increases the relevance of your marketing efforts but also helps build trust and credibility with your audience. With personalized targeting, businesses have higher chances of delivering the right marketing messages at the right time: the key to effective B2B marketing campaigns. 

Types of Data Segmentation

There are several different types of data segmentation that you can employ in your B2B business strategies. These include demographic segmentation, firmographic segmentation, behavioral segmentation, and psychographic segmentation. 

• Demographic segmentation involves dividing your audience based on demographic factors such as age, gender, location, and income. This type of segmentation allows you to target your marketing efforts toward specific demographic groups that are most likely to be interested in your product or service. 
• Firmographic segmentation, on the other hand, focuses on the characteristics of the companies within your target audience. This may include factors such as company size, industry, geographic location, and revenue. 
• Behavioral segmentation involves dividing your audience based on their actions and behaviors. This may include factors such as purchase history, website interactions, and engagement with your marketing materials. 
• Psychographic segmentation takes into account the attitudes, interests, and values of your audience. This type of segmentation allows you to target your marketing efforts toward those who share similar psychographic traits, allowing for a more personalized and relevant messaging approach. 

Key Benefits of Data Segmentation 

Creating well-defined data segments has benefits across the entire business. Let’s look at why your company should pay close attention to your data segmentation practices. 

1. Lead Generation 

Your sales and marketing teams use data every day to help them decide on who to contact and how to target them. By knowing who your best customers are, what they care about, and what type of communication they’re most receptive to, your team can use their time more productively. You can also use your findings to score leads and prioritize well-qualified accounts in your pipeline. 

2. Improve Cold Outreach Success Rate 

Data segmentation can help your team discover accounts that fit your SQL criteria before even contacting them. This is highly achievable with the right demand generation partner to identify leads. By knowing firmographic and technographic details about a company, and who the key decision-makers are, your sales team will save a ton of time. Your success with cold email will increase due to the targeting and messaging improvements based on your learning. 

3. Prioritize Support Requests 

Knowing your key customers will help your customer support team prioritize their workload. The more specific you are about who your customer is, the better you’ll be able to find them. Your support team will know what your best customers look like, and from there, can prioritize support requests, as well as provide feedback on key accounts to account reps. This will help extend the Customer Lifetime Value (CLTV) of your best customers even further. 

Challenges to Effective Data Segmentation 

Segmenting your data is a crucial task, but many organizations struggle to do it well. 

Research conducted by Experian found that 94% of companies find data segmentation challenging. 

Many companies struggle to use data to help with personalization.

They outlined the top three struggles that companies have, which are as follows: 

1. Gaining insight quickly enough 
2. Having enough data 
3. Inaccurate data 

Let’s look at how you can overcome these challenges. 

1. Gaining Insight Quickly Enough 

Segmenting your data takes time. If it takes too long, everyone in the company gets impatient, and you won’t see the benefits. To tackle this challenge, you should start by asking yourself a key question. 

Why are you segmenting your data? 

Once you know your ideal outcome, the data can be organized and used immediately. 

This will allow your sales team to have access to accurate and segmented prospect lists, helping them contact the right people at the right time. 

Your marketing team will be able to craft new campaigns and refine their targeting based on real insights. 

2. Having Enough Data 

Not sure if you have enough data to use database segmentation? In most cases, you almost certainly do. 

If you have paying customers, you can gain key insights from your existing customer data. 

By identifying your best customers (as we mentioned previously, looking at the customers with the highest CLTV is a good indicator), you can identify trends. 

For example, let’s say that all of your best customers use a key feature more often than your other customers. It would be fair to then assume that these customers all have similar pain points. Your sales team can then address that common pain point in their cold emails or calls to close more deals. 

You can also look at data collected on your website by Google Analytics, or by the audience most responsive to your Facebook Ads. These data sets can help to inform your data segmentation practices and improve your targeting. 

If you’re a startup without any customers and a low amount of traffic, then a lack of data will clearly be a challenge. But, you can ensure your sales outreach is as personalized as possible by segmenting your B2B data lists. 

3. Inaccurate Data 

With 28% of B2B sales emails leading to a bounce, there’s a chance your contact database contains bad data. As you know, accurate data is key to a successful sales team. Without it, finding and contacting good leads will be impossible. 

You can take steps to reduce your data inaccuracy and save your team time in the long run. 

Firstly, you can use data validation best practices. Data validation will help your team have access to clean, accurate data. 

Use email validation tools to validate contact data before sending a cold email campaign to prospects. 

With DemandScience, you don’t have to worry about doing this yourself. We regularly validate and clean our B2B contact data (we can even tele-verify your contact lists) to ensure they’re accurate and ready to be used in your sales and marketing. 

How Should You Use Data Segmentation in Practice? 

Now that you know what data segmentation is, its benefits, and how to avoid common pitfalls, you’ll want to know how you can translate your data segmentation efforts into action. 

Here are some practical steps you can take when you have well-segmented data. 

1. Refine Your B2B Buyer Persona 

Any great marketing strategy starts with knowing your buyer persona in detail. 

Segmented customer data will help show you exactly what your ideal customer looks like. You will be able to identify key traits and characteristics of your buyer persona, and then use a tool like DemandScience to find more similar prospects. 

This will save your sales team the time usually spent on identifying qualified prospects and sourcing accurate contact data. 

2. Improve Your ABM Campaigns 

With any Account-Based Marketing (ABM) campaign, well-defined targeting is key. 

Bad targeting wastes time and money. 

Great targeting enables your team to generate more leads and spend more time closing deals. 

Good data segmentation is a critical first step to ensuring accurate targeting. The more relevant your outreach is to the recipient, the more successful your ABM campaigns will be. 

DemandScience demand generation solutions, such as Content Syndication, Display Advertising, and Email Marketing, are all tailored to target your most ideally matched accounts. It assists in identifying the most suitable accounts, initiating ABM advertising interactions, and expediting your sales pipeline. 

3. Segment Your Customer Database 

We’ve referred to this idea a few times throughout the article, but we should further clarify the benefits of segmenting your customer database. Clear knowledge of who your best customers are has benefits for every single part of the company. 

If you sell a digital product, you can segment your customer database by behavioral indicators. These can include things like how often users return, their most-used features, how often they buy new credits, when they’re most likely to upgrade their subscription, and so on. 

All these data points provide you with insight into who your key customers are. 

How Data Segmentation Helps Sales and Marketing Teams for B2B Businesses 

Data segmentation helps sales and marketing teams better understand their audience and their ideal customer profiles (ICPs), allowing for more consistent and effective messaging and communication. Furthermore, data segmentation allows for more accurate measurement and evaluation of marketing campaigns. Tracking the performance of each segment separately, both marketing and sales teams can identify which segments are responding most positively to your messaging and adjust your strategies accordingly. This data-driven approach helps optimize your marketing efforts and drive better results. 

Conclusion: Data Segmentation for A More Accurate Targeting 

There’s no doubt that data segmentation is going to help your business grow. 

Data segmentation is crucial for B2B business strategies because it allows you to move beyond a one-size-fits-all approach and instead focus on delivering personalized experiences to your target audience. 

Your sales and marketing team will have a newfound clarity in all of their work. More time can be spent identifying and closing key accounts that will be a great fit for your business. 

Ongoing and regular data segmentation is key if you want to do this well. Ensure that it’s embedded in your company culture and that everyone is on board. 

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