Data Segmentation: The Ultimate Guide
December 29, 2019
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
Let’s dive into the article.
What Is Data Segmentation?
First, let’s define what we mean by Data Segmentation in this article.
Data segmentation is 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, data segmentation isn’t only useful for sales and marketing.
We’ll also look at how 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.
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 team 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.
Data Segmentation in Practice: Higher Revenue, Happier Customers
You should be using data to enable your team to make better decisions.
If you’re not sure whether to spend more time on data segmentation, then this case study from the Harvard Business Review could help change your mind.
It highlights key ways that companies can achieve growth when they start segmenting data.
The case study looks at a successful company, Hill-Rom, whose growth had slowed down.
By segmenting their data based on key criteria they were able to discover that their best customers spent 40% more than the average customer.
They used their insights to add a renewed focus to their sales work, leading to revenue per employee growing by 11%. Their customer satisfaction levels also increased.
We recommend reading the case study if you’re on the fence about spending time improving your data segmentation practices. If you decide that you want to see similar results, come back to this article and we’ll show you how to get started.
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 will be particularly easy if you’re using a B2B data supplier like DemandScience 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.
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.
They outlined the top three struggles that companies have, which are as follows:
- Gaining insight quickly enough
- Having enough data
- 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 data 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
Great marketing 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.
This allows you to create highly personalized campaigns that convert well across all mediums, whether it be cold email, cold calling, or PPC campaigns on LinkedIn.
The more relevant your outreach is to the recipient, the more successful your ABM campaigns will be.
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.
There’s no doubt that data segmentation is going to help your business grow.
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.