Heard Enough About Big Data? Try Little Data Instead
Much has been written about Big Data, including the insights that can be gleaned from thousands or millions of data points, especially in the data-rich B2C market.
But what about Little Data? What can we learn from just a few data points? And when is Little Data appropriate in market, competitive, and buyer research?
We’ve often been asked how many data points are “good enough.” Clients who have worked in consumer marketing expect answers with phrases such as “confidence level” and “margin of error.”
B2B Data Analysis to Understand the Marketplace
In B2B research, where researchers typically capture detailed buyer feedback through several methods of triangulation, getting as few as 10 data points per program can provide significant insights into:
- Buyer reluctance to purchase from vendors
- Areas of strength that should be replicated as best practices throughout the organization
- Competitor strategies and tactics that could impact success over the long term
“How can 10 data points be enough?” many clients ask, often with incredulity building in their voices.
Why Little Data Works in Understanding B2B Markets
- B2B markets tend to be highly specialized, with buyers and companies dictating specific requirements from their vendors. Buyers know with great certainty what they want and expect in terms of product functionality, pricing, and service and support.
- Pricing in B2B industries is generally uniform within markets and segments, with few variations in pricing models or pricing levels. Companies have figured out how to make acceptable margins while still remaining competitive.
- Sales teams who sell complex B2B platforms are experts in their fields. Not only are they conversant with the technical specifications of the solutions they’re selling, they also have a firm grasp of markets, competitors, and pricing.
- B2B account teams are typically polished and professional when interacting with demanding and sophisticated buyers. The best B2B reps have been selling for decades but remain current with ongoing training and education.
- Researchers who study B2B markets typically use a variety of techniques to understand deal dynamics and outcomes. Rarely are senior buyers who were involved in complex, multi-month (or multi-year) buying cycles sent a simple online questionnaire with a handful of questions, as is common in consumer surveys. Rather, researchers probe in great detail about buyer perceptions in a variety of areas, including:
- Product/service quality:
- Comprehensiveness of the offering
- Specific features and functionality critical to buyer success
- User interface, ease of use, and intuitiveness for end users
- Sales team effectiveness:
- Understanding buyer needs
- Product knowledge
- Knowledge of the buyer’s industry
- Perceptions of vendors:
- Long-term financial viability
- Service and support
- Vendors’ experience with the customer’s industry
- Pricing levels
- Pricing models
- Pricing complexity
- Product/service quality:
eBook: B2B Quantitative vs. Qualitative Data
If you’re not using qualitative AND quantitative data to improve your sales opportunities, you’re flying blind. You wouldn’t make a high-dollar business purchase without reviewing the data, right? Without research, rating assessments, and an evaluation, you know it could be a costly mistake.
Online Surveys and Telephone Conversations in B2B Research
When online surveys are used in B2B research, they’re usually accompanied by follow-up telephone conversations, allowing researchers to zero in on the key strengths and weaknesses of short-listed vendors, as well as detailed reasons for vendor selection and non-selection.
- Because B2B researchers are typically experts in specific industries or segments, intelligent follow-up questions can be asked to truly understand deal outcomes.
- B2B buyer interviews are often compared to dinner party conversations—they’re more akin to a back and forth dialog between two industry experts than a scripted telephone interview rotely recited by an untrained researcher.
- Because interviews are usually recorded, researchers are free to think about—and not worry about writing down—what the respondent is saying, encouraging thoughtful follow-up questions.
Turning Data Into Action
Based on the characteristics of the B2B market and using the techniques outlined above, researchers and managers can clearly see trends and patterns in the data very quickly. Below are a few stand-out examples from our history in B2B research using Little Data to generate big insights:
- A technology start-up with the best solution offering available learned after just a handful of interviews that buyers were choosing the long-term industry stalwart for fear the start-up wouldn’t be around over the long term. Buyers didn’t want to start over with their vendor selection process in 12 or 18 months if the start-up was acquired or merged with another player.
- A healthcare company discovered after just eight interviews that cost and flexibility were top-of-mind for its customers. It also learned that competitors were trying to establish relationships with its installed base to expose potential fissures and dislodge it in competitive campaigns.
- A network storage company learned after nine interviews that customers perceived it as a nimble player in the market. However, customers also expressed concern about the company’s lack of 24×7 global support and missing integrations with key industry players.
- A property casualty insurer discovered after just four interviews with key customers how to position itself to retain their business, including making changes to its policy renewal timing, modifying its pricing strategy, and emphasizing its competitive differentiators.
While collecting more data over time helps to fill in blank spaces and turn unresolved questions into answers, companies can and should take action on key learnings they uncover in their Little Data research projects, especially when the feedback is consistent and provides detailed guidance on next steps. Always waiting for more and better data will only frustrate buyers and allow competitors to take advantage of indecision and inaction.
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