Growth-Hacking Tools and Managing Costs and Pricing

Growth-hacking tools

Finding quick success isn’t just the imperative of an AI/ML product manager but of all product managers and entrepreneurs. Figuring out the best way to make money, increasing brand awareness, and finding quality leads is what growth hacking is all about. Although most products won’t go viral overnight, there is some method in the madness of investing in the tools. They all get us closer to the information we need to make present and future decisions in a way that’s informed by what works and what our customer truly wants from us. We went over some broad categories of products that certainly help with growth hacking and finding success with our AI/ML product previously, but there are so many valuable tools out there that don’t fall into those categories per se.

Advanced tools for product growth

• Products such as Expandi allow us to use LinkedIn for social selling campaigns.

• Crystal Knows uses AI to craft personality profiles to provide insights into behavior and sentiments.

• Landbot helps us build chatbots to interact with our customers in-app or on our platform.

• Hotjar allows us to see heat maps and other analytics of where users’ cursors move in our product.

• Usability Hub helps us conduct UX research with real users.

• Fomo helps us build credibility with our brand through transparency and social proofing.

• Leadfeeder helps us turn our page visitors into leads.

Balancing market fit and managing AI costs

There are endless products out there to help companies achieve the right balance of product market fit. The route we choose will be some combination that keeps the gears of development going but also allows us to stop and reflect. Processing choices that have been made allows us to assess whether or not those choices are bringing us closer to our ultimate goal of successfully commercializing our AI/ML-native product.

Here, we will discuss the costs that contribute to the expense of managing AI pipelines, as well as their impact on pricing. While incorporating AI might come with some efficiencies that should, theoretically, make our price point lower, the total cost of managing an AI program internally is quite high. That cost is often passed onto our customers because it contributes to the overall cost of running our product.

Managing costs and pricing

Formulating a pricing strategy will be a highly personalized experience that will involve a number of factors, from the comparative prices of our competition to the operating costs for managing our AI/ML infrastructure and workflows. We will briefly cover the various aspects of AI product management that impact costs and how to use this knowledge to inform our pricing strategy so that we’re aware of the main contributors to our AI/ML program costs.