We’re living in an increasingly individually researched world where the permutation of goods and services is decided by consumers. While customers may chat with online site agents, many of today’s purchases are influenced through online research with limited human interaction. Purchasing decisions on goods and services are influenced by the opinions of independent subject matter experts, as well as online user recommendations and trusted friends. As a result, businesses have been quickly retooling their marketing and sales departments over the past few years to align their go-to-market capabilities along the path of this new consumer journey.
Marketers and sellers have had a lot of help during this transition, using CRM, MAP and modern web tools to facilitate online customer engagements. However, the effort has been largely focused around promotion, positioning and direct to consumer online channel development more than pricing and profit optimization. Many firms still don’t truly understand the behavior, interests and value that their customers experience from the products and services they purchase. As a result, pricing or offers are still highly simplistic and largely remain oriented around simple broad-segment retail pricing strategies.
Arjuna’s ExactAsk algorithm leverages A.I. and M.L. capabilities to optimize revenue production in the emerging environment of complex consumer purchasing and pricing decisions.
Arjuna Solutions has been named to our Top 25 Machine Learning Companies List in 2018 because of their approach to solving the issue of optimizing pricing and revenue production in today’s complex consumer pricing environment. Their ExactAsk algorithm along with an innovative go-to-market strategy facilitates easy B2C adoption of the technology at scale. These two capabilities have materially differentiated the firm from their peers across the A.I./M.L. solutions market, enabling the firm to grow quickly with an increasingly diverse array of clients.
“Our self-learning algorithm has demonstrated the expertise to make highly effective personalized pricing decisions for consumers at scale that are consistently superior in delivering stronger business results than the current pricing practices employed by human actors. It’s the combination of our pricing prowess, the ability to deliver these decisions instantaneously at scale, and a very simple go-to-market strategy for our customers that has allowed us to develop a very compelling business with AI as a stand-alone product.” notes Adam Treiser, CEO/Founder of Arjuna and Professor of Decision Sciences at the Johns Hopkins University Whiting School of Engineering.
This may well be the breakaway moment that we forecasted for A.I. in 2018, as the A.I. industry’s preeminent solution providers begin delivering compelling, achievable and pragmatic business results for their clients in a profitable and reasonably short period of time.
Michael Gorriarán, SVP at Arjuna Solutions and former Microsoft executive indicates, “Our client’s customers are accepting ExactAsk offers at a higher rate, and much more rapidly than before. The individually personalized price points we provide seem to be better aligned with the value of the experience that consumers are personally deriving from the underlying product/service permutation that they are creating and buying. This value-based consumer pricing orientation is better aligned with the nature of today’s more complex purchasing decisions that consumers are making. Whether it’s for concert tickets, technology purchases or even when financing the political ambitions of the candidates that they support, consumers are moving away from simple low-cost options with small profit margins for providers. The new model is one of consumers enjoying the freedom to configure or influence the product/service mix they prefer to buy, and then reflecting the value they experience in the individual price points that Arjuna can deliver at scale. Customers are very willing to pay for the value they experience, and this is reflected in the revenue growth that our clients are experiencing.”
This does not seem to be a point of conjecture, as Arjuna’s experience in specific client tests over the past two years shows compelling evidence that ExactAsk regularly outperforms human actors in delivering stronger revenue growth in today’s complex pricing environment.
The solution that Arjuna has been delivering to market over the past two years has been applied to solving the conundrum of optimizing fundraising for the breadth-donors of non-profit agencies. Arjuna’s clients such as PBS, Special Olympics, Charity Navigator and Habitat for Humanity have traditionally depended upon their CEOs or Business Development professionals to research and cultivate relationships with major donors. However, the right formula for efficiently pursuing the rest of their donors was not apparent.
“We were thrilled to see how the performance of ExactAsk has improved during the past two years. We’ve produced more real-world uses and value of AI than any other provider in the industry at this time. We’ve come to appreciate the incredible value that individually calculated donor “Ask Amounts” can bring to a non-profit agency’s fundraising efforts. Our portfolio of clients have realized an average revenue lift in contributions of 21 percent within first year and 71 percent within two years” noted founder Adam Treiser.
Michael Gorriarán, SVP with Arjuna Solutions indicates, “While Arjuna is only at the beginning of enabling non-profit agencies to advance their respective causes more efficiently, we are thrilled with the early acceptance of ExactAsk, and we are confident that using Artificial Intelligence will become a common business practice in non-profit fundraising.”
Arjuna Solutions’ ExactAsk Key Points:
Uses AI to determine an individualized ask amounts for each donor
1. Applicable to any direct mail, telemarketing or email campaign
2. Optimized for acquisition, reactivation/lapsed and existing donor campaigns
3. Uses the donor and gift data most nonprofits already track and store in their databases as well number proprietary factors and publicly available data to optimize “Individual Ask Amounts” per donor
4. No system testing, system integration, training, consulting fees, data fees, or other setup costs
5. Average increase in the value of donors is > 21 percent within first year, and over 70 percent in two years