As companies grow, their ability to understand their customers is diminished, which ironically impedes their ability to continue down the path of growth.
CRM databases in HubSpot and Salesforce simply become too big. 46% of contact center decision makers estimated their contact centers to grow by 5%-10% in the next year, which for many is an unsustainable rate.
Engagements with those customers are spread out among more people within your organization. You begin to target more customer personas and, somewhere along the line, your ability to connect on a personal level with every customer falls by the wayside.
It’s part of the growing pains that most companies go through as they expand. Many often find themselves unprepared for the large-scale data operations considerations that are required when you begin to collect higher volumes of customer data. It’s a new challenge that must be met head-on, as all companies must come to grips with growing customer data management needs.
A lack of focus on customer data audits, quality initiatives, and enrichment programs leave companies underprepared to serve their customers.
Luckily, with the right data quality initiatives in place, organizations can leverage proper customer segmentation to create 1:1 personalized conversations with every prospect and customer.
Let’s start by defining customer segmentation.
- What is Customer Segmentation?
- What Are the Benefits of Customer Segmentation?
- 4 Tips for Effective Customer Segmentation
- How Insycle Can Help with Customer Segmentation
- Sign Up for Insycle Today, Free
What is Customer Segmentation?
Customer segmentation is the practice of segmenting and filtering customers based on common data-based characteristics. Segmenting customers helps marketing teams to speak more personally to each prospect or customer, identify the best opportunities in their sales pipeline via lead scoring, and provide better experiences to their customers.
Customer segmentation uses several different types of data to sort and filter customers into collective groups, typically based on their targeted buyer personas:
This data includes but is not limited to:
- Demographic data.
- Geographic data.
- Behavioral data.
- Psychographic data.
- Customer journey data.
Using the right data points, you can effectively group similar customers and prospects. This allows you to deliver more personalized messages and deliver a better pre and post-sale experience to customers through platforms like HubSpot and Salesforce.
For instance, if you sell your B2B solution to marketing professionals, the needs of a Marketing Director and a Marketing Manager would differ greatly. Delivering the same messaging that highlights the same pain points for two customers with different concerns will alienate one of those two customers over time. Customers like to feel understood. To understand them, you need a data-driven approach.
Customers expect a personalized experience that takes previous interactions and information they have provided your organization into account. If you overlook that, you can bet that a competing company will deliver what you can’t and win them over as customers.
What Are the Benefits of Customer Segmentation?
We’ve covered the basics of how customer segmentation benefits organizations that invest in it. However, the real-world benefits of segmentation run much deeper than you might expect, touching nearly every corner of an organization’s operations.
A few reasons why all organizations should invest in proper data management for segmentation include:
Create effective customer profiles for use across teams.
Customer segmentation doesn’t just serve your marketing automation campaigns and messaging. It serves nearly every department in your company. Every person that touches data in your HubSpot, Salesforce, or Intercom accounts with benefit from accurate and detailed customer profiles.
Sales will develop a deeper understanding of specific customer types, with data to back up their assertions. Support and success teams will have more persona-specific context to use in customer interactions. Engineering will better understand the needs of important customer personas.
Draw conclusions about engagement for specific customer personas.
Who are your most engaged customer types? Who are the least? Without proper customer segmentation in your CRM and marketing software, you can’t effectively analyze your buyer personas.
Any conclusions you make about different types of customers without proper segmentation in place would be based entirely on anecdotal information and not a truly data-backed approach.
Identify new business opportunities.
The potential analysis that comes from deep customer segmentation can open your eyes to new opportunities that would otherwise go unnoticed.
For instance, maybe you find that a previously untargeted customer segment tends to convert at very high rates with high levels of engagement, making what was once viewed as an opportunity that wasn’t worthwhile into a major driver for growth.
Segmentation doesn’t only let you better understand your current customers. It also helps you to identify new customers and customer types.
Leverage a data-backed product strategy.
If you offer a software product, it is common to find that different customer segments may use your product differently. If you sell marketing software, a social media manager is likely to use your social media features while your advertising team would use advertising management features.
Without proper segmentation, it’s impossible to truly understand your data beyond broad generalizations. In other words, you can see what is going on, but can’t draw insights into why it might be happening without breaking down your customer data into smaller groups.
Deeper analysis through segmentation will help you to dig deeper than surface assumptions. For instance, a surge in usage of the advertising side of your platform might drive you to flesh out the features of that platform. But deeper segment analysis might show you that the surge in usage was driven by a segment that really doesn’t need the features you would otherwise plan to roll out.
Customer segmentation leads to a deeper understanding of usage data that should play a key role in defining your product roadmap.
Improve churn and retain customers.
Segmentation improves your messaging and understanding of key customers. You’ll be able to speak more directly to their biggest concerns through your automated messaging. You’ll be able to deliver product information and offers that are more relevant to them. You’ll can spot important customers with low engagement levels and step in to see how you can support their goals.
Ultimately, segmentation means a better experience for your existing customers and lower churn levels over time. 86% of buyers will pay more for a better brand experience, but only 1% feel that companies meet their expectations in this regard.
Better understand performance with key customer personas.
Without segmenting your customers, you can’t analyze your performance in specific segments. You might see an upturn in revenue, but can you connect that to performance with a specific customer segment beyond an educated guess? Data often produces insights that are counter to what we assume.
Is your growth driven by marketing managers or marketing directors? How has your marketing and sales performance differed between mid-sized companies and enterprise engagements? Does your sales team typically perform better with prospects in a specific age group? Why?
These are the answers that a complete customer segmentation program can unlock. But those answers are only useful with quality data driving those insights.
4 Tips for Customer Segmentation Strategy
With an understanding of the benefits of customer segmentation, you can now begin looking at how to implement a customer segmentation strategy within your organization.
Before diving head-first into creating different buckets for organizing your customers, consider these tips to ensure you segment customers effectively:
#1) Define Problems to Solve with Segmentation
What are the exact problems you are hoping to solve with segmentation? By outlining these, you give yourself a plan for moving forward.
These problems can and should cross departments. Marketing may want a better idea of how their campaigns influence specific segments. Sales may want to create separate optimized sales sequences for different customer types. Engineering might want a better idea of what customer feedback should be prioritized, based on data.
Each of these problems-to-solve requires different information. Know what you want to solve so that you can collect and analyze data with those problems in mind.
Defining the problems that you want to solve is a key component of an effective customer segmentation strategy.
#2) Choose Effective Data Variables for Segmentation
Choosing the right variables ultimately decides how effective your segmentation program is. To start, make sure that you are choosing data variables that are collected for a majority of your customers.
For example, choosing to segment companies by revenue is not an effective choice when you primarily work with private companies who do not publish their financial data.
The variables that you choose should reflect meaningful differences in the types of customers that you serve.
#3) Improve Data Collection for Important Variables
Once you know the ideal variables to use for segmentation, you can look to improve your data collection initiatives for those data points. Then, you can create more targeted customer segments around that data.
You might decide to add new inputs to customer onboarding questionnaires. Or forms. Or instruct marketing teams to ask new questions in the qualification process.
In some cases, you may need to invest in data enrichment programs. Collecting higher volumes of reliable data will improve segmentation outcomes and give you more angles to work with.
Improving your data collection is critical for an effective customer segmentation strategy.
#4) Install a Data Quality Initiative
Your segmentation program will only deliver genuine insights if your data is reliable. Data quality must be a primary concern for your segmentation strategy to bear fruit. The more targeted your customer segment, the more tightly you can craft your messaging.
Ensuring that your data is accurate, properly formatted, standardized, and consolidated is necessary to ensure accurate segmentation and well-defined customer segments.
To improve your data quality for segmentation, check out Insycle.
How Insycle Can Help with Customer Segmentation
Insycle is an incredibly powerful customer data management solution for companies looking to improve customer segmentation or install new segmentation initiatives.
Insycle gives you complete control over your data, allowing you to solve common data errors and ensure your customers and accounts end up in the correct segments through a powerful suite of data quality and analysis tools for your customer segmentation process.
Improve segmentation accuracy with consistent formatting.
Let’s say you want to segment your contacts by their job title, a common variable for B2B companies.
But you have a problem — the way that different job titles are named are not consistent. Your CEO segment might have their position expressed in a few different ways within the data:
- Chief Executive Officer
- Acting CEO
You have to make sure that all of these prospects end up in the same bucket, or else they’ll just be floating in your CRM without being properly categorized. This leads to missed opportunities. With Insycle you can reliably identify and target every customer segment that moves the needle for your business.
Insycle can help you to create consistency and standardization throughout your customer data. Not just with job titles, either — with any field! Another example includes company names where the inclusion of “LLC” or “Inc.” is a common standardization issue.
Location-based segmenting by city, country, or state has its own standardization issues as well. Take state, for instance. If you want to segment customers by state, there will be multiple ways that “New York” might be expressed in your data:
- New York
- New York State
- New York, New York
When segmenting, you want to make sure that all of these customers end up in the same bucket. However, without standardized data, you can be sure that some will be missed in your customer segmentation process.
Insycle makes it easy to ensure that all of your important segmentation variable data is formatted consistently, not just as a one-time fix, but on a scheduled ongoing basis.
Cleanse customer data and identify common data errors.
Insycle can help you identify inaccurate and problematic data in your database that might impede your segmentation efforts.
With Insycle you can:
- Identify incomplete customer data and records with missing values.
- Find inaccurate customer data (invalid phone numbers, name fields with numbers, and other bad data).
- Identify and smart-merge duplicate records in bulk on HubSpot, Salesforce deduplication, and Intercom.
- Remove redundant records and consolidate fields.
- Automate data cleansing processes to run on an hourly, daily, weekly, or monthly basis. Complete hands-free data cleansing!
- Preview changes before they go live to ensure you don’t overwrite or remove critical customer data.
Associate stray contacts with companies and deals.
Missing an important stakeholder for an account in ABM can completely throw off your segmentation. Ensuring that those associations are in place are critical for delivering consistent messaging and experiences to all stakeholders across an organization.
Additionally, certain stakeholders may actively affect the customer segments that an account is placed in.
For instance, segmenting contacts based on company-level properties like “Number of Employees” would necessitate that you have accurate associations for all of your existing prospects with the right companies.
Filter and aggregate customer records to evaluate potential segments.
Insycle allows you to filter customer records in your database and aggregate records based on any field in your HubSpot, Salesforce, or Intercom database.
This feature is extremely powerful for segmentation because it allows you to analyze potential segments before deploying them across your operations. Or, you could use this feature to break down existing segments into sub-segments for marketing automation purposes.
Segmentation delivers a deeper understanding of your customer base, but you need to be able to effectively search your data in your customer segmentation process.
Being able to quickly filter and evaluate customers based on any data field is incredibly powerful for fleshing out deep segmentation.
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