An AMEND approach to pricing strategy for property management
The Challenge of Pricing
“Come on down!” shouts Bob Barker, as a very excited audience member dances their way to the stage. The Price is Right TV show drew people in with their challenge of guessing the price of products. Contestants see a product, and without much context, estimate a price that is as close to, but not over the correct price to win.
The prizes and production elements add to the fun, but this mirrors decisions businesses make every day. Determining price for a new or existing product can be extremely difficult for businesses and teams, especially without visibility to the right market data.
On one of our recent projects, we sat down with a client with substantial experience in property management in urban, walkable neighborhoods to really evaluate what goes into their right price, and more importantly, what doesn’t.
The question at hand for a local property management company: Are our apartment units and commercial spaces priced at the optimal amount? With a number of properties spread across several urban neighborhoods with differing levels of renovations, finishes and amenity offerings, how do we determine the appropriate pricing levels?
Why pricing is important
Property management has faced many challenges over the last two years, so the question was especially relevant. Our client had internal data and years of property management experience but wanted to also utilize market data to complement that knowledge and experience, and understand an unbiased perspective on pricing.
Pricing their offerings too low creates a potential risk for losing out on revenue potential. Pricing offerings too high creates a potential risk for extended vacancies and losing out on revenue potential.
Therefore, AMEND used a variable-based approach with external market data, coupled with qualitative input of key pricing factors from our client, to get them to that sweet spot of pricing.
We knew we needed external market data to understand current-state demand. We found multiple data sources we could tap into for our analysis. Once we pulled the data together, we ran a Stepwise AIC model to apply variables such-as number of bedrooms, number of bathrooms, square footage amount, and others to tell us about their importance in relation to price. After working with our client to better understand the variables, we specifically applied the results by zip-codes to analyze one-level deeper and capture the variation across Cincinnati and Northern Kentucky neighborhoods. After assessing the results and rolling out the math, we felt confident in sharing a data-driven pricing strategy with our clients.
We were able to compare the pricing recommendations from the model output to their current pricing per property in Microsoft Power BI to easily evaluate the differences. This gave our client a starting point when deciding where to make pricing changes first. The data model and Power BI dashboard automatically update to pull in the most recent information.
The information elevates our client from a being in a price-guessing situation to making better price-informed decisions utilizing the data analyzed specifically for their properties and zip-codes. The Power BI dashboards also included a “what-if analysis” to enter potential future properties or spaces to determine the recommended price before hitting the market for the first time.
Give us a call!
The concept we used for property management pricing could be applied to other pricing strategies as well, such as construction management, real-estate, new or existing products, and more. The key is to understand what variables really matter to the price and focus in on those variables. That also provides an understanding what doesn’t matter, confidently guiding your team to focus on the aspects that are going to add the most value.
We love this type of work. It is exciting for us and our clients. We want you to have the same energy and excitement out of the right price as The Price is Right constants who just won a new car. If you would like to explore data-driven pricing strategy and recommendations, get in contact with us by filling out the form on our contact page!