Engaging relevant, high-quality data is a critical action for contemporary marketing and sales teams to take when crafting personalized content for their potential clients. Often, organizations have access to enormous datasets which, left unorganized, can be more of a hindrance than a help. In order to be useful, your data needs to be sorted and refined to provide you with the information you need to drive an effective campaign.
Analysis of cut-off portions of a geometric figure or object.
Segmentation analysis allows you to sort data into recognizable categories that describe specific client profiles. With this information in your back pocket, you can more easily create relevant, timely messaging and pathways for potential clients.
In this post we’ll discuss how segment analytics work and how you can make them work for your organization.
Segmentation analytics help you recognize and categorize potential clients who are interacting with your digital platforms or engaging peripheral programs (search engines, etc.)
In B2C segment analytics, the goal is to define different customer categories based on specific characteristics and observe which demographics are buying what products, when, and how often. Having this information enables companies to provide relevant, targeted messaging to a smaller number of people, often with better results, rather than a generic campaign aimed at a wider group with little in common.
B2B segment analytics will also categorize clients based on firmographic information and can help you design relevant marketing, sales-conversion and retention strategies dependent on the category of the target business. (Learn more about firmographic data in our other post: Firmographic data.)
Which segments are considered vital will depend on the precise needs of your business, and you can create or remove categories as those needs change and develop. In the next section, we will cover how you can go about creating data segments.
Which segments you need to create will depend on the firmographic data, as mentioned above. Firmographic data sets are generally easy to gather and won’t require the same observation or direct-approach research you might need to employ in a B2C study. Firmographic data is also accurate over a much longer time period, except in stages of major growth or transition.
Firmographic data sets typically include a company’s industry, size, location, revenue, and growth trends, and your segments may reflect those attributes directly. However, depending on firmographics alone can result in vague or mixed categories which only provide useful information half the time. Do incorporate firmographics into your analytics, but consider creating more precise segments based on:
Segmentation analytics have the benefit of determining how to prioritize a target or lead. The most efficient strategies target the best-qualifying potential clients first. Or, if you’re trying to break into a new market, you can target specific segment organizations for better growth opportunities. It can also allow you to effectively identify new-on-the-scene businesses who fit into predetermined segments, minimizing the contact to sales-conversion period.
This also determines how you can best serve your potential client. Segments based on client need, industry, and business type will help you narrow down how your product provides unique customers with specific solutions. You will also better understand how to communicate this to individual clients.
Segment analytics help to provide you with actionable information by answering a few critical questions.
Segment analytics help you to convert firmographic data into meaningful information by categorizing potential clients and allowing you critical insight into the needs and behaviors of an organization. And Intricately can take it a step further by helping you understand how to use that information to your best advantage. Request a personalized demo today to see if Intricately is right for your business.
Are your clients making promises and not following through? Read about a kind of data that can help you solve this problem here: B2B behavioral data.
In this chapter, we predict trends for 2020 based on our analysis of the global adoption of APM.