I noticed that AppFolio's pricing had remained stagnant for years, creating a significant disconnect between the price and the actual value our product delivered. This outdated pricing structure failed to account for the diverse needs of our customer segments, including Residential, HOA, and Commercial, which meant we were potentially leaving money on the table. Additionally, the absence of a product-led growth (PLG) strategy was evident, and our customer support costs were escalating, particularly as SMBs were consuming a large amount of support resources.

Action:
To tackle these challenges, I initiated a project to divide the product into 15 distinct feature areas. I conducted a MaxDiff analysis to gauge our customers' preferences, utility, and willingness to pay (WTP). Based on the insights gathered, I categorized the features into four quadrants: Core, Broad Value Driver, Niche Value Driver, and Low Priority. I also performed a comparative price analysis to understand how competitors charged for similar features. I engaged with our sales teams and customers to validate our findings and ensure we were addressing actual needs. Ultimately, this led me to create three new pricing packages—Core, Plus, and Max—while also offering four broad value drivers as add-ons tailored to specific customer requirements.

Resolution:
Although I faced initial resistance from various teams regarding these changes, the new pricing strategy yielded impressive results. Within the first year, I saw our average revenue per unit (ARPU) increase from $1.87 to $2.55, translating to a remarkable $7.5MM revenue boost.

Our pricing and feature strategy categorized offerings into three tiers: core, plus, and max. A standout upsell was the Leasing Signals feature, which assists property managers in pricing their rentals accurately, especially given recent legal issues surrounding Realpage. When core users visited the rent setting page, we aimed to upsell them with a free trial of this add-on, as they were already inclined to purchase this valuable data, much like users seeking salary information on Levels.fyi. This approach led to a 13% trial sign-up rate, although the trial period was limited to seven days. After a user subscribed to the add-on, we introduced upsell opportunities for the Plus plan, testing various messaging strategies such as "See what you’re missing for just a little bit more" and "You’re already using X, and the full Plus plan is only x% more," resulting in a 1% conversion rate from Core to Plus. For those who did not convert, we initiated a drip campaign after a couple of months to highlight their usage of the purchased add-on and showcase the percentage of Plus customers benefiting from additional features.

At AppFolio, a vertical B2B SaaS company, our software helps property managers manage the entire tenant lifecycle, from lead acquisition to move-out. I identified a significant issue with our payment offerings, as they were not well monetized, and I needed to determine the value and appropriate pricing for these features. 

My goal was to better understand the value of our payments service and how undeveloped features might appeal to our customers. This effort aimed to drive incremental upsell revenue and clarify how to package certain features effectively, whether as usage-based, within SaaS subscriptions, or a mixed approach

To tackle this, I used a MaxDiff analysis to categorize our payment features into four quadrants: Core, Niche, Broad Value, and Low Priority, which informed how we should price and tier these features (as add-ons, per use, or included in the SaaS tier). I also performed a Price Sensitivity Analysis to gauge WTP for each feature by asking questions such as, “How likely are you to use Feature X at various price points?”

The findings from these analyses revealed several core features that we weren’t charging for but had high willingness to pay, leading to a substantial increase in revenue of $XMM. This project taught me valuable lessons about determining product value and effective pricing strategies.

Appfolio has a 2nd product. Investment management. Investment management is used by investors who want to manage property P&L, stake-ownership etc. It’s an asset tracker and an asset performance tracker. This test was targeted at owner/investor operator PM’s as they are the most likely to need these features

Our cross sell motion was for the Max tier. We offered API’s and a direct integration with AIM. We would display these when the customer exported rent rolls (likely to compute P&L in excel). We saw a 2% trial conversion rate (AIM is much more expensive than APM)

Situation : Appfolio sells property management B2B software. Maintenance and repairs of properties are a large part of Property Management. To facilitate smoother completion of work orders Property Managers can invite vendors to manage work orders and pay invoices on completion of the job. Appfolio has > 1MM vendors on the platform and 71% of these vendors are SMBs with < 5 employees and 80% of them are family owned and operated.. These vendors are unable to get loans for primarily three reasons 1) Smaller businesses not served by banks and 2) Improper accounting 3) Lack access to banking infrastructure. During interviews I heard this as a pain point many times and I decided this was worth pursuing even though I had no real understanding of the space. 

Task : After conversations with my manager I read a lot more about invoice underwriting learning from existing competitors, their challenges, loss rates, more interviews, partner banks forming a detailed point of view on the space and product. I also continue to collect snippets from interviews and surveys with vendors to showcase the importance of working on this. 

I also worked on developing an ICP. Our ICP was 

• SMBs with <5 employees

• At least 50% of their business is from Appfolio

• Annual revenue between $50k-$200k 

• Loan amounts between $5-$20k

• Work with multiple property managers (on or outside Appfolio)

This ICP was developed based on conversations with 50+ vendors. Larger vendors either didn’t require loans, had adequate banking relationships or were typically tied to larger property managers as staff (i.e. salaried employees). The ICP was also developed based on a painted door test which asked vendors if they would be interested in a small business loan. Our hypothesis is that this segment of users would like to expand their business but typically lack capital and time to invest in sourcing loan products. Furthermore, most commercial banks will not serve this segment of customers due to loan size

I also did some basic financial modeling to show the potential impact and how this aligns with Appfolio’s strategic objective and presented it to our VP who was the exec sponsor of this project. The dev team was folks I had worked with on payments and it was a small team of engineers and a eng leader. Having clearly defined needs, how this strategically aligns, data from interviews with vendors and their needs. We opted to go with an embedded finance lending partner and the Embedded lending product went live in Feb 2024. This was the first embedded finance product that Appfolio launched in several years in a matter of a few short months! The larger strategy here though is becoming the Vendors system of record (ie their full invoicing platform. In order to build that out we needed a hook. Loans are a hook, the more standalone business you do with Appfolio the larger your loan.

At AppFolio, a vertical B2B SaaS company, our software serves property managers throughout the entire tenant lifecycle, from lead acquisition to move-out. Property managers cater to three main customer types: renters, owners, and vendors.

In my role focusing on embedded finance growth, I concentrated on identifying strategic opportunities and launching new products to enhance our offerings. For instance, I explored initiatives such as providing deposit accounts for property managers to boost retention, offering loans to vendors, and facilitating mortgages for owners—all aimed at increasing platform stickiness for all user types. My key learning was : Driving a deeper wedge with new growth products + key advantage of not having to worry about acquisition

• At AppFolio, a vertical B2B SaaS company, our software helps property managers manage the entire tenant lifecycle, from lead acquisition to move-out. In my role, I focused on growing our renters insurance business, which is sold to renters. My efforts concentrated on four key areas:

  1. Strategic Initiatives: I explored opportunities to introduce new insurance products to expand our offerings, such as layoff insurance, auto insurance, and homeowners insurance.

  2. Top-of-Funnel Strategies: I developed methods to attract more potential customers, utilizing tactics like improved onboarding processes and targeted email marketing campaigns.

  3. Segmentation: I conducted research and surveys to understand our customer demographics and motivations for purchasing insurance. This helped us personalize the experience based on customer segments, enhancing conversion rates.

  4. Funnel Optimizations: I focused on improving the conversion rate throughout the sales funnel, specifically during the checkout process. This included A/B testing checkout pages, information pages, pricing structures, and introducing features like Apple Pay for convenience.

  Additionally, I collaborated with our partners to transition our payment gateways from Payeezy to Checkout.com.

  Through these efforts, I learned that small changes can lead to significant impacts, and the effectiveness of different strategies can be unpredictable. I also discovered that segmentation is crucial for personalization and that convenience can drive decisions for a small percentage of users. Overall, these initiatives resulted in a 17% increase in funnel conversion.

Appfolio offers renters insurance to tenants of property managers. However a tenant can purchase their own insurance and upload the policy. Test 1 : Do people click (+8% click rate, curious!) 

Test 2 : Prior to expiry do people click (+27% click rate, low purchase rate as prices were higher)

Test 2 : Used data from above to make a case to insurance co to provide better options. 3 months of testing this drove an incremental $250k in policies

At AppFolio, a vertical B2B SaaS company, our software assists property managers in managing the full tenant lifecycle, from lead acquisition to move-out. I noticed that tenants of our property managers were purchasing renters insurance from third-party companies. During the renewal cycle, we had the opportunity to target these tenants with our own insurance offers, as we had visibility into when their policies were due. We used OCR and glean out expiry, pricing, bundle and then a month before expiry we would show the user a message “Hey, your policy is expiring, see a comparable policy”

My primary responsibility was to develop creative upsell experiments such as the above one aimed at encouraging customers who had not purchased renters insurance from us to consider our offerings. Through various strategies, including upsell experiments, painted door tests, and data analysis, I aimed to identify effective ways to convert these potential customers.

As a result of these initiatives, we achieved an impressive revenue increase of $XMM, demonstrating the effectiveness of our targeted upsell strategies.

Situation: Our renters insurance product was facing a significant decline in user retention rates, with many users purchasing insurance and canceling their policies roughly two months later. This decline posed a serious threat to our revenue and caused considerable stress for leadership due to lost revenue and compliance issues for property managers.

Task: I was tasked with identifying the root cause of this retention issue and implementing solutions to enhance user engagement and retention.

Action: I conducted a thorough analysis of user behavior data to pinpoint patterns and drop-off points, discovering that 90% of cancellations occurred in the second month. I reached out to about 100 users to understand their reasons for canceling. It became clear that when users logged into the portal to pay rent, they encountered their insurance policy details alongside a cancellation option. Most users, unaware of the requirement to maintain insurance, were confused by the cancellation link, which provided no contextual information. To address this, we implemented two key changes: we moved the cancellation button out of the portal flow, replacing it with a "Manage Policy" button that allowed users to access their options more fairly. Additionally, when users clicked the cancellation link, we informed them of their legal obligation to maintain their policy and that canceling would enroll them in a less protective Landlord Liability policy.

Result: After implementing these changes, we achieved a 15% reduction in cancellation rates within the first month. The redesigned product experience not only educated users about their obligations but also clarified the potential consequences of canceling. I also coordinated with the engineering team to develop a Slack alert and email notifications for canceled policies, reminding customers to upload a new policy if needed.

At Appfolio, we recognized a significant opportunity for growth by addressing the lack of customer segmentation in our renters insurance product, which was drawing around 500k monthly visitors without any personalized offerings. I spearheaded an initiative to understand our user base better by conducting a survey of 5,000 respondents to gather insights on their preferences related to age, location, family status, and insurance needs. This data enabled me to perform a K-means cluster analysis, revealing eight distinct customer segments that we had previously overlooked.

These segments included:

• College Students: First-time renters primarily interested in basic liability insurance.

• Young Professionals: Price-sensitive individuals looking to protect their electronics and furniture.

• Families: Customers needing broader coverage for children’s belongings and higher personal liability limits.

• Retirees: Older, price-conscious renters seeking peace of mind for their personal possessions.

• Pet Owners: Renters requiring coverage for pet-related liabilities.

• Expensive Equipment Owners: Individuals with high-value items needing specialized insurance.

• Roommates: Shared renters needing coverage tailored to their situations.

• Luxury Renters: High-end tenants requiring higher coverage limits for valuable assets.

To ensure the accuracy of our findings, I triangulated survey data with our policy records, identifying trends in customer purchasing behavior. We discovered that over 70% of policyholders were either overserved or underserved. This insight led to the development of a machine learning model to predict the types of policies specific segments would buy and their willingness to pay.

The implementation of these strategies resulted in a 4.7% increase in conversion rates and a 14% increase in average policy price. Additionally, we established a robust feedback loop in our product development process, which includes Design/Concept → Feedback → Finalize Design → Build → A/B Testing → Iterate. This iterative approach ensures that we continually refine our offerings based on real user feedback, setting the stage for sustained growth.

Situation / Task: When I joined the renters insurance team, we were solely focused on haphazard experimentation without a clear hypothesis. The team lacked a Product Manager, and since A/B testing was perceived as “cheap,” we ran experiments and launched initiatives without understanding what worked and who purchased our insurance. Additionally, our efforts were made without consideration for future plans or how our learnings could guide our direction. In short, there was no long-term connection between our activities and the company's needs; effectively, there was no strategy.

Action: I adopted a three-pronged approach:

1. Short Term: Understand the business and the experiments we were conducting.

2. Medium Term: Conduct research and segmentation using K-means clustering to inform our top-of-funnel strategy.

3. Long-Term Horizons:

   • 2-Year Horizon: Focus on upselling and increasing renters insurance sales.

   • 5-10 Year Horizon: Explore additional products we could offer:

     • For Tenants: Layoff protection, auto insurance, identity theft protection.

     • For Vendors: General liability insurance.

     • For Owners: Homeowners policies.

     • For Property Managers: Small business insurance.

Short Term (3 months): I sought to understand the business and the experiments we were running, identifying our goals and key performance indicators (KPIs). We established our North Star metric—Total Commissionable Premium. I created experiment templates, emphasizing the necessity of clear hypotheses for our experiments.

Medium Term (6 months): I inquired about our customer base, and it became evident that we lacked clarity on who our customers were. I developed a research plan to recruit users from within and outside our pool, supplemented by surveys as part of the product. I requested a budget from management to conduct user research and run surveys to ascertain user preferences. While the team initially did not understand the value of this, I encouraged their support.

The insights we gained shifted our direction and improved management's perception of our efforts. After conducting several interviews, we learned that our product was primarily serving three segments, but it was not adequately addressing their unique needs. In essence, we were offering an average product for average users:

• Younger Users (18-30): Seeking cheaper policies with a desire for minimal coverage but needing clarity on what they were purchasing (price-sensitive and knowledgeable).

• Younger Users (18-24): Looking for affordable policies, generally indifferent about the specifics (time-sensitive).

• Older Users (30+): Likely with children and more valuable possessions, these users wanted comprehensive coverage (price-conscious but with higher stakes).

Additionally, we discovered that around 50% of users did not purchase from us due to a lack of awareness. This insight drove me to focus on building a top-of-funnel acquisition channel to ensure we didn't lose potential customers. We had substantial opportunities to enhance our website, streamline the tokenized flow, and improve product insurance linking.

Long Term (2-10 years): The advantage of vertical software is its potential for low customer acquisition costs (CAC). For context, AppFolio has approximately 6 million tenants on the platform, with only about 10% penetration (500,000-600,000 active policies generating around $100 million in revenue at an average policy price of $200). A critical strategic question for me was why we couldn’t capture a larger market share. Given pricing and insurance partner/provider challenges, I explored potential partnerships to reduce costs, enhance customer choices, and improve plan offerings.

I also began evaluating additional insurance products we could offer both to tenants and other customers on the platform, such as:

• For Tenants: Layoff protection, auto insurance, identity theft protection.

• For Vendors: General liability insurance.

• For Owners: Homeowners policies.

• For Property Managers: Small business insurance.

Result: By clearly articulating a long-term strategy, the team felt motivated, and I was able to secure additional resources to pursue various initiatives. This structured approach created a sense of direction and viability for our long-term strategy.