Published by Jessica Weisman-Pitts
Posted on November 20, 2024
8 min readLast updated: January 28, 2026
David Bartenwerfer
David Bartenwerfer is a prominent figure in the field of real estate investment and asset management as well as the application of analytical rigor to corporate strategy and operations. As the Co-Founder and Chief Technology Officer of REALbasis Inc., Bartenwerfer has pioneered the application of quantitative methods to real estate, enabling investors to achieve above-market returns through advanced data analytics. His expertise is not limited to real estate; he is also the founder and principal of Quantum Consulting and Technology, where he has applied strategic thinking and technology across various industries for nearly two decades.
Based in San Francisco, David Bartenwerfer’s career includes significant roles at major companies such as The Boston Consulting Group, Charles Schwab, and Yahoo! His academic background, with an MBA from Stanford University and a BS in Systems Engineering from the University of Virginia, and has provided a strong foundation for his work in strategy, technology, and operations.
In this interview, we delve into Bartenwerfer’s insights on the role of analytics in real estate, the challenges in lead management, and the future of customer retention, among other topics.
The Genesis of REALbasis Inc. and the Role of Analytics
What inspired you to co-found REALbasis Inc., and what role do analytics play in its success?
Bartenwerfer: REALbasis Inc. was created to bring quantitative rigor to real estate investment and asset management, which enables investors to uncover markets and micro-markets that can produce above-market returns with limited risk. Analytics are at the core of everything we do—comprehensive data aggregation, predictive models, risk assessment, market simulations, and optimization modeling enable us to forecast returns and risk with precision and guide investment strategies based on data-driven insights.
Revolutionizing Customer Retention Strategies
How does Quantum Consulting and Technology approach customer retention differently than traditional models?
Bartenwerfer: At QuantumCT, we see retention as more than just a metric. Rather than focusing solely on defection rates, we analyze granular customer dynamics. By understanding the nuances of purchasing patterns, we can identify opportunities to drive long-term growth, anticipate customer needs, and build more predictive models to forecast client behavior with greater precision.
Addressing Challenges in Lead Management
What are the biggest challenges in lead management for businesses today?
Bartenwerfer: One of the primary challenges is that lead management often falls into a gray area between marketing and sales, which can create inefficiencies. A fragmented process results in delayed follow-ups and wasted resources on unqualified leads. By integrating analytics with process and clear ownership, businesses can centralize lead data, quantify the value of leads, qualify leads more effectively, and ensure each one reaches the right channel at the right time.
The Importance of ROI in Sales Strategy
What advice would you give companies on integrating ROI calculations into their sales strategy?
Bartenwerfer: My advice is to treat ROI as a product, not just a tool. Effective ROI models require a dedicated owner to ensure usability and credibility so they resonate with prospects. It’s about building a compelling, quantified narrative that speaks to each decision-maker’s concerns, from business units to finance teams.
Measuring ROI in Decision Making
What advice would you give companies on trying to predict ROI as a part of their corporate strategy for making investments in technology?
Bartenwerfer: investment in technology is critical, whether to shave costs, generate revenues, or outpace rivals, investment in technology is an integral part of most corporate strategies. Successful investments can be game changers for companies—but a colossal failure can be a game changer as well. The sad fact is that far too many technology investments go badly wrong, destroying profits, careers and sometimes entire companies. Successful investments deliver benefits that outweigh the costs, hence the popularity of return on investment analysis.
However, today’s mainstream methodologies and frameworks for measuring ROI have proved to be insufficient; this is particularly true for technology initiatives. Business leaders who want to increase the likelihood of the success of their investments should think beyond ROI and employ a more robust process that drives organizational clarity and accountability while uncovering the potential for both hidden profit and hidden risk.
Measuring ROI for Marketing Organizations
Speaking of ROI, what advice would you give marketing organizations when they are trying to predict ROI?
Bartenwerfer: Marketers are facing demanding times. The emergence of Web 3.0 and other tech has changed the way consumers interact with brands. These new ways of engagement represent both a challenge and an opportunity for Marketing organizations to re-consider how they allocate resources. Also, as senior management applies increasing pressure to deliver evidence justifying marketing investments, marketers are also expected to objectively measure the ROI of their efforts. Yet, even seasoned marketers may be overwhelmed to develop a competency around quantitative analysis while meeting conventional marketing demands.
When other departments invest, a relatively simple ROI analysis can be performed to justify the expense. Increased revenues demonstrate the effect of a new product; decreased costs prove the value of new technology. But Marketing efforts are more complex and inter-dependent rendering such a simple analysis limited and incomplete. Most experts agree that it can take between seven and nine “touches” before a customer will actually make a purchase, requiring marketing programs to overlap and work together to increase the likelihood of an eventual sale. This complexity makes determining the individual impact of each program difficult to ascertain. Furthermore, marketing programs have multiple objectives and engage prospects at different stages of their decision process. And while these initiatives aren’t in conflict, their diverse natures make it challenging to objectively evaluate investment options.
Enhancing Customer Acquisition with Predictive Analytics
How can companies use predictive analytics to enhance customer acquisition?
Bartenwerfer: Predictive analytics helps companies streamline lead scoring and prioritize high-potential leads for immediate action. It enables businesses to forecast customer behaviors more accurately, segment their leads effectively, and optimize acquisition costs by targeting resources where they’ll deliver the most impact.
Learning from Experience at Top-Tier Organizations
What’s one key lesson you’ve learned from working with top-tier organizations like The Boston Consulting Group and Yahoo!?
Bartenwerfer: Agility is essential. Each of these companies excelled by fostering a culture of continuous improvement. To stay competitive, businesses must be willing to adapt their strategies quickly, whether through new technologies, data analytics, or restructuring processes to align with changing market dynamics.
Trends Shaping the Future of Customer Retention
What trends do you see shaping the future of customer retention?
Bartenwerfer: Customer retention is evolving by employing more predictive analytical tools to identify potential customer defections before they happen, and then proactively engaging with those customers to reduce the likelihood of defections. Companies are beginning to leverage data not just to react to churn but to anticipate it. Technologies that can pinpoint behavioral changes early on will redefine loyalty programs, helping businesses intervene before customers defect.
The Intersection of Systems Engineering and Business Strategy
How does your background in systems engineering contribute to your work in business strategy and analytics?
Bartenwerfer: Systems engineering, similar to the field of operations research and operations management, instilled a mindset of the application of analytical rigor to operational challenges, for the purposes of increasing efficiency and optimizing impact, which translates well into business strategy. Whether I’m managing a team or developing a quantitative model, I approach each challenge holistically, considering how each part affects the whole and looking for solutions that maximize value across the board.
Misconceptions About Data in Decision-Making
What do you consider the biggest misconception about using data in decision-making?
Bartenwerfer: One misconception is that data is a definitive answer. Data can guide us, but it’s not infallible. Interpretation matters, and a strong understanding of context and intuition is crucial for making sound, data-driven decisions. For example, many variables in business have both an expected value and a variance. By only focusing on the former, business leaders risk making poor decisions by not considering the riskiness of their options. Thus businesses must balance quantitative insights with experience and critical thinking.
Continuous Innovation in the Field
What drives you to continue developing innovative methods in your field?
Bartenwerfer: Curiosity and a commitment to making measurable impacts. I’m always fascinated by how different models can be refined to yield new insights. It’s rewarding to develop strategies that tangibly improve profitability and efficiency, and I’m driven by the challenge of finding unique solutions that help clients thrive in competitive landscapes.
Overcoming Barriers to Technological Adoption
What are the primary barriers companies face when adopting new technologies, and how can they overcome them?
Bartenwerfer: Resistance to change is a major hurdle. Often, organizations are comfortable with their existing processes and wary of the disruption that new technologies might bring. To overcome this, it’s crucial to build a strong case for the benefits of technology adoption—how it can enhance efficiency, reduce costs, or open new revenue streams. Providing training and support can also ease the transition, ensuring that employees feel equipped and confident to use new tools effectively.
David Bartenwerfer’s insights continue to inspire innovation in real estate asset management and beyond, demonstrating the transformative power of data-driven strategies. His work exemplifies how quantitative methods can unlock new potentials across diverse sectors, offering a blueprint for businesses striving to remain competitive in a rapidly evolving landscape.
Bartenwerfer’s approach to integrating analytics in real estate and business strategies highlights a new frontier in quantitative analysis. His innovative methods continue to shape the future of investment and customer engagement, setting a benchmark for excellence in the industry.
Quantitative analysis involves the use of mathematical and statistical methods to evaluate financial and investment opportunities, helping investors make data-driven decisions.
Customer retention refers to the ability of a company to retain its customers over time, focusing on maintaining long-term relationships and reducing churn.
ROI, or Return on Investment, is a financial metric used to evaluate the profitability of an investment, calculated as the net profit divided by the initial cost of the investment.
Predictive analytics involves using statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data.
Lead management is the process of capturing, tracking, and nurturing potential customers (leads) through various stages of the sales funnel until they convert into paying customers.
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