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Lucy is an integrated data application platform for the American Express ecosystem, providing developers with data and application abstractions to simplify product development effort while satisfying complex enterprise requirements.
Data Application
Keap(formerly Infusionsoft), is a company that mainly offers software solutions and service in client management, sales, and marketing process, and email automation. Each year, Keap serves more than 26,000 small business owners (150,000 users) to help them automate and grow their business.
Overview & Intro
Keap Marketing Strategy Research
Key words: pricing sensitiviy, positioning, packaging, pricing stragtegy,
The goal of this research is to develop an effective value proposition and pricing strategy Keap. Through this research, we have confirmed that Keap is in the right direction for pricing and packaging. Small Business Owners(SBOs) across personas value Keap's core functions, such as Client Relationship Management(CRM), automation, and payments. This also indicates that, potentially, Keap can charge more for its full-featured products with refined pricing and packing strategy. New opportunities have also been identified in product features like analytics and reporting. Research findings have also suggested that most participants valued SMS much less than current Keap customers.
A combination of qualitative and quantitative research methods had been used to develop persona profiles as well as pricing and packaging strategies.
Key research questions and areas:
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How to identify high-value customers to position effectively?
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What are the valued features of product packaging that each subset of small business owners wants?
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What are these types of small business owners willing to purchase a robust, sales, and marketing software?
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How to develop a Value-Based pricing strategy?
Key methodologies
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Potential customers and prospects survey
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Data-driven buyer personas/profiles
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Relative preference analysis
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Pricing sensitivity meter(PMS)
Role and Responsibility:
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Lead pricing, packaging, and positioning marketing research
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Design and develop a research framework based on given resources and tools
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Data analysis, synthesis, and data visualization
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Presentations of research findings
Roadmap & Framework
Before developing a research framework,
Develop a roadmap and timeline for the research project
To ensure the research finding can be delivered within the given timeframe, I have created a project status report and roadmap, and keep it updated as the project moving forward. I was quite lucky to work with all talented people and delivered the final result successfully.
Figure 1. A snapshot of the final status report and overall project timeline/roadmap. The status report was used to ensure each team member had resource and time they need to finished the task. This also help provide transparency between each team member and ensure the process went smoothly.
Research Methods & Framework
An overall research framework was created to help structure the data collection and analysis process. Refined buyer personas and key segments had been developed based on collected data and ongoing analysis. Through mapping out value metrics, feature metrics, and pricing sensitivities to each buyer persona, recommendations for product packing, positioning, and pricing strategies are made.
Key research and analysis methods used:
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Survey
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Cohort analysis
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Factor analysis
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Relative preference analysis
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Pricing sensitivity meter(PMS)
Figure 2. Research framework. As shown in the graphic, small business owners who live in North America are target Keap customers. During the survey, we had asked their business info along with questions that help analyze their price sensitivity and value metrics. Pricing sensitivity and value metrics are segmented by their business situation, which helped create three main buyer personas. Business recommendations are made based on each buyer persona's business growth, value metrics, and pricing sensitivity.
Pricing sensitivity meter:
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The Indifference Price Point represents an optimal price point. It is the point at which the price is optimized for adoption and monetization
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The Optimal Price Band represents the band within which to price. The lower end of the band optimizes for adoption, the higher end optimized for monetization
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The Likelihood to Buy is asked on a scale from 1(very unlikely) to 5 (very likely)
After analyzing the collected data, two key segments had been used to sort out data
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New contacts added per month: 0 - 10; 11 - 50; More than 50
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Likelihood to Buy: 1(very unlikely) to 5 (very likely)
Research Execution
Data Collection
Survey
After drafting the inital survey structure and questions, I worked with key stakeholders, product researcher, and survey platform provider to refine and lanched the survey. Thanks for all the support and help I had been given along the way, 162 valid participants had filled out the survey within three days. This helps us us build the base for future persona and pricing research iterations with greater amout of samples.
Link to survey: https://my.helio.app/t/01EJEJ69V071AX85ZPN84Z41DD?preview=true
Cohort analysis, Factor analysis
Identify key segments to create data-driven buyer personas
Once we collected needed raw data, I started to work with survey platform provider to identify the key segments that helps us develop valid personas. After some frustrations and struggles, new leads added per month had been used as one of the key segments to create data-driven buyer personas. Additionaly, I built a secondary customer profile based on their willingness to pay.
Figure 3. Snapshots of working in progress spreadsheets
Buyer personas
Figure 4. Buy personas. Starting our Sarah: Small business owners who have 0 - 10 new leads/contacts added monthly. Their annual revenues are mostly between $0 to $100,000 and the number of employees is mostly between 0 - 5 employee(s). Most of them have been in business for 0 to 10 years. Scaling Sam: Small business owners who have 11 - 50 new leads/contacts add monthly. Their annual revenues are mostly between $51,000 to $3,000,000 and the number of employees is mostly from 2 to more than 100 employees. Most of them have been in business for 2 to 15 years. Established Ellen: Small business owners who have more than 50 new leads/contacts added monthly. Their annual revenues are mostly from $101,000 to more than $3,000,000 and the number of employees is mostly from 10 to more than 100 employees. Most of them have been in business for 2 to more than 20 years.
Feature and value metrics analysis
Mapping out key metrcis to customer profile
To better understand small business owners' value metrics, we had asked participants to choose features they preferred most and least within a list of current Keap features. Relative preference scores were calculated using: (# of times feature is most wanted - # of times features is least wanted)/n.
Figure 5. Overa aggragate relative preference chart. X- Axis: Indicates the preference magnitudes. Positive magnitudes indicate preference and negative indicate disfavor. Meaningful: ≥(±)0.15; Slight preference(disfavor): (-0.15 〜 -0.05) & (0.05 〜 0.15); Indifferences: -0.05 〜 0.05
Overall aggregate relative preference
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Figure 6. Aggregate relative preference by buy personas. Starting our Sarah: For SBOs who are relatively new to their business (0 - 10 new contacts added per month), Invoice and Payment is the most valued feature. Scaling Sam: For SBOs who are seeking to grow their business(10 - 50 new contacts added per month), CRM is the most valued feature. Establish Ellen: For SBOs who are relatively matured in their business (more than new contacts added per month), CRM is the most valued feature.
Aggregate relative preference by buyer personas
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Figure 7. Aggregate relative preference by LTB. LTB - 4.4: For SBOs who have shown a relatively high interest in purchasing a robust, sales, and marketing software, CRM, Report & analytics, Itergreations, and lead collection tools are some features they value. LTB - 3: For SBOs who have not shown a strong interest in purchasing the software, Marketing automation and CRM could be features that convince them to purchase. LTB - 1.4: For SBOs who have relatively low interest in purchasing the software, CRM, Invoice & Payment, and Report & analytics could be areas for Keap to provide help and education.
Aggregate relative preference by LTB(Likelihood to buy)
Pricing sensitivity analysis
Identify the indifferent price point and optimal price band
In the survey, we asked the participants the following four questions to discover small business owners' price sensitivity when it comes to purchasing.
At what monthly price would you consider a robust sales & marketing CRM software to be:
too expensive to consider purchasing for your company?
getting expensive, but you would still consider purchasing for your company?
a bargain - a great buy for the money?
so inexpensive that you would question the quality and not consider it?
Figure 8. Pricing sensitivity - Starting out Sarah. Indifferent Price Point is the point at which the same amount of respondents think the software is getting expensive as think it is a bargain. The Optimal Price Band is a range of possible prices. The low-end point is where the same amount of respondents think the software is too cheap as think it is getting expensive. The high-end point is where the same amount of respondents think the software is too expensive as think it is a bargain.
Figure 9. Pricing sensitivity - Scaling Sam. Indifferent Price Point is the point at which the same amount of respondents think the software is getting expensive as think it is a bargain. The Optimal Price Band is a range of possible prices. The low-end point is where the same amount of respondents think the software is too cheap as think it is getting expensive. The high-end point is where the same amount of respondents think the software is too expensive as think it is a bargain.
Figure 10. Pricing sensitivity - Established Ellen. Indifferent Price Point is the point at which the same amount of respondents think the software is getting expensive as think it is a bargain The Optimal Price Band is a range of possible prices. The low-end point is where the same amount of respondents think the software is too cheap as think it is getting expensive. The high-end point is where the same amount of respondents think the software is too expensive as think it is a bargain.
Research Findings
Establish detailed target customer profiles
After mapping out value metrics and pricing sensitivity to each buy persona, three main customer profiles have been successfully established. Additionally, key business info have been grouped by their likelihood to buy to provide insights of what kind of small business owners are interest in purchasing a robust sales and marketing software and what serves they are looking for in such a software.
Link to final presentation: https://drive.google.com/file/d/1absbVnMBku81b-TG0ImrXKQEtb_giYH9/view?usp=sharing
Suggestions & Next Steps
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To attract small business owners to purchasing, Keap needs to lean heavily into CRM and automation in its marketing and sales messaging.
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Update exist pricing and packaging strategies to ensure each product better matches its targeted customer group.
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Re-evaluate resource and effort that has invested in developing SMS related features.
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Update Keap sales and marketing messages to showcase small business owners on how to incorporate SMS into their sales and marketing channels.
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Further iterations on persona and pricing research are needed as this study has a limitation in the number of participants.
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