Vendors of data and machine learning products above $20,000 ACV (annual customer value) traditionally require a dedicated sales professional who answers three questions for potential buyer:
Why should the buyer change what they are doing?
Why should the buyer change now?
Why should the buyer choose us?
During these turbulent times in which meeting face-to-face to discuss customer needs is nearly impossible, self-serve can be an additional revenue channel with minimal costs. At kindlyAnswer.me we have developed tools to help data and machine learning vendors answer those three questions via a new channel:
Self-Service Benchmarking and Delivery
Many businesses currently do not use 3rd party data or machine learning products. Thus illustrating the range of use cases available to them and sparking their interest in your data/machine learning is an essential first step. To achieve that we have assembled a comprehensive list of use cases for each job role:
Action: Sharing this list with a potential prospect may ignite their interest to maintain their professional development and to continue learning about emerging data and machine learning solutions.
While there can be a broad range of answers to the question of why a customer should act now; in today’s current environment businesses are looking to stabilize revenue and to reduce costs.
To ensure value for money, we enable all solutions to be benchmarked and tested before final purchase. Giving the customer a working solution into their hand crystallizes their benefits and encourages immediate purchase.
Action: As a data/ml vendor you should upload your existing API to make it easily available to our buyers. This new channel: self-serve benchmarking and delivery enable immediate answers to the question ‘why now?’.
Last but not least, the data and ml vendor must clearly position their solution as the superior choice for the customer use case. We rank most of the available solutions allowing you to position yourself as the leader in a 3rd party benchmarking study based on the actual accuracy of the data / machine learning itself (1 star <20% accuracy, 5 starts>80% accuracy).
Action: Not all customers want the best answer (5 stars) thus aiming to win the competition can be a false objective. Try to create the most cost effective solution for a particular use case and thus win against the competition.
It is well understood that every business needs machine learning and data products. However, the current explosion of vendors introduced a paralysis of choice. Traditionally the sales professionals aim to resolve this by making their product more accessible and transparent. However, with the current restrictions on travel and face to face meetings, most buying decisions of high-value products require self-serve benchmarking and delivery.
If you would like to benchmark your API and list it on our marketplace please reach out ([email protected]) or upload your model: