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1. Crafting the messaging for our flagship AI products

The new AI-first messaging reflecting on the Freshworks website

Objective ****

In 2023, we made major Gen AI upgrades to Freddy AI, Freshworks’ AI software for customer service. These changes would also level up our flagship product offering, Freshdesk Omni.

I was tasked with revamping the core messaging and positioning for both these products. The idea was to clearly communicate our upgraded AI product offering, establish ourselves as leaders in the ‘AI for customer service’ space, and differentiate ourselves clearly from competitors in a crowded market.

Effort ****

Here’s how I went about crafting the messaging for Freddy AI and for Freshdesk Omni.

• Collaborate with the Product team to understand capabilities: I had a regular cadence with the Product Managers working on the Gen AI features for Freddy AI. By being part of the product brainstorm sessions, I learnt the key uses cases we were solving for. As the product neared completion, I got a hands-on experience of how the product worked. This was crucial for crafting the messaging, as I could experience the product from a customer’s perspective.
• Get inputs from Sales on which pitches work: I spoke to various Sales leaders to understand which parts of our current AI pitch worked and which didn’t. I also learnt more about how customers perceived AI in customer service and the top use cases they were looking to address. I realized that while our current AI pitch was good, it wasn’t too differentiated from our competition. Customers weren’t able to understand how we stood apart. They also felt our current pitch was too feature-heavy and technical. This made it difficult for them to understand its value propositions without investing a lot of time into learning the product themselves.

• Understand product differentiators from Engineering: The ‘AI for customer service’ market is crowded, especially after Gen AI became mainstream. To be able to understand how we truly stood apart, I collaborated with the Engineering team to identify key differentiators for our product.I learned that our training data sets of billions of customer service interactions set us apar from generic players. Our security and privacy compliances and checks meant we were an enterprise-friendly AI product. We were also a zero-code platform that was easy to implement, with a strong innovation roadmap for the product. Our customers could also ‘talk’ to the AI within the product and pass on instructions, similar to the ‘Siri experience’. We needed to highlight these differentiators front and center in our messaging.

• Scope out how the competition messages similar products: I conducted a thorough study of how Freshworks’ competition messages their AI. I spent a lot of time on Zendesk, Salesforce, Hubspot, etc’s website and attended their webinars. This helped me understand the basics of what customers expect. It also gave me ideas on areas where we could do better than them.

• Draft the v1 of the messaging: With all the research done, I created the first draft of the messaging document. It talked about the different personas/role we build for (customer service leaders, managers, agents, and admins). I also added persona-specific messaging, talking about each role’s pain points and how Freddy AI solved for them. Our differentiators were infused into the messaging at all points. All our claims were backed up with actual feature capabilities and real-life results from existing customers.

• Gather feedback from small customer and internal groups: I took the v1 of the messaging document and ran it by key stakeholders internally for their views. I also presented the messaging to very small customer groups, as part of the Freshdesk Customer Advisory Council sessions. I gathered feedback from ~20 customers on what they thought of the messaging, and got great inputs from them on what could be improved.I learned that explaining what’s possible is not good enough. Everything has to be backed up with how the product actually delivers those results. The customers also suggested that I add more real-life use cases and analogies when crafting the messaging.

• Finalize and rollout the new messaging: Once that was done, we finalized the messaging and rolled it out internally and externally. The messaging doc served as the source of truth document for any team that wanted to build any content around AI. For ex: the Digital Marketing team used it when creating display ads. The Content team used it to create ebooks. The Solution Engineering team used it to add talking points to their product demos.

We also infused the messaging into all internal and customer-facing marketing assets, such as pitch decks, the website, competitor battle cards, etc.