Segmentation is used to get an up close view of the market. Based on categorizing customers with specific characteristics, segmentation can offer deep insight about an industry and the companies within that industry. So how do you get started?
A couple of quarters have passed since the echoes of the last product launch celebration. One day, your executive informs you that things are not looking good. The competition is gaining market share and Sales says that the product that you built does not meet customer needs. As the product manager, you mentally race back in time – you have spoken to different types of customers, created buyer personas and diligently worked with your stakeholders in marketing and sales. So what went wrong?
The temptation is to look at the long list of enhancements. While features may be a part of the issue, it could just as easily be product pricing, go to market strategies, and field enablement efforts. To understand potential problem areas, it is often helpful to take a step back and think about big picture questions like
Segmentation has traditionally been used by marketers to get an up close view of the market. It is based on the principle of identifying variables that predict characteristics and behavior, using a mix of quantitative and qualitative approaches to categorize customers with specific characteristics. Identifying these variables and collecting the data is considered to be time consuming and tedious. However, applying the principles of segmentation can offer deep insight about problems at hand and even help come up with potential solutions.
We will look at nine segmentation variables in three categories that will help you perform quick and effective root cause analyses.
An industry segment typically refers to a grouping of similar businesses like telecommunications, financial services, etc. The traditional segmentation approach uses attributes like revenue, geographic location and type of business. While these attributes provide board categories, we can dig deeper and incorporate more useful details by focusing on attributes like size, substitutes and sales cycle.
Traditional numbers like industry growth rate and market size are a good start but looking at spending and budgets can provide more realistic data. Industries have different propensities to spend on a given problem and their annual spending budgets reflect this. Gaining insight into size of the spending budgets by different industries is a good litmus test for the pricing model.
For example, some industries have bigger capital expenditure budgets and meager operating budgets. In these industries, a term-license that has a minimal impact on the smaller operating expenditure budget is a good fit. Another consideration would be selling in an appliance model where hardware and software are paired together.
Some industries are early technology adopters. Understanding the adoption rate and the typical roadblocks to adoption will provide insight into whether the current challenges are a result of incomplete features or alignment of industry specific field enablement to aid in faster adoption.
Product manager often talk to customers and conclude that the product truly solves the right problems. However, one of the most commonly overlooked areas involves understanding available substitutes. The cost of switching is often underestimated, unless one of the drivers for change is a regulatory or policy requirement. Understanding the regulations of a given industry and the business policies around compliance, social responsibility and governance can provide a realistic measure whether the product will be switched from existing substitutes.
Sales cycles are often thought of towards the end of a product development lifecycle. The evaluation of the sales cycle will provide insight into entry points that have worked in the past and establish patterns that could be exploited for future deals. In addition to entry points, understanding existing sales relationships is key and how they are leveraged in a sales cycle is important. For example, to increase market share, features are often introduced to create up-sell or cross-sell opportunities. knowledge of the relationship between your sales team and the customer’s line of business provides an understanding if the current relationships exist for selling into an adjacent line of business. As an example, a testing product focused on quality departments can have features that are relevant to developers. This will mean that the sales team would need to have entry points both into QA and development organizations. However, if the sales team has relationships with QA managers, that relationship may not be as easily leveraged in industries where development and QA are separate, silo organizations.
To get specific information on size, substitutes and sales cycle related attributes, the win-loss analysis is usually the best source of information. The sales team has detailed information about spending budgets and signature authority. The person who approves and signs the purchase order is indirectly providing the amount of money he/she has in their budget to solve the problem. Combining the information about the title of the person, the industry and the size of the deal, it is possible to infer the actual budget.
To understand adoption, a survey can be used to ask about the last major product adoption or upgrade. This question usually reveals how long it takes for industries to upgrade their solutions. Salespeople also have knowledge about sales cycles and asking them about their supporters at their customers will reveal the source of their relationship strengths. Once the information is available at the company level, a site like Yahoo! Finance can use used to find the industry.
Dutta Satadip is a Director of Product Marketing and Management at MarketTools where he is responsible for setting the product vision and executing strategy. He has previously managed a portfolio of products at HP Software that included product incubation and business development. Dutta has held several leadership roles in marketing, product management, and engineering management at HP and SAP. He has an MBA from the Haas School of Business, UC Berkeley and MS in Computer Science from Virginia Tech.