It’s high time to reimagine customer support based on first principles - no legacy assumptions, no retrofitting antiquity. Organisations everywhere are struggling with SaaS sprawl, growing complexity, and data locked in rigid silos. These problems don't fade away with time - they only compound as teams grow in size and complexity.
It is time to adopt a CRM that grows with you - one that is comprehensive, scalable, and offers a unified solution that encompasses the entire customer lifecycle including sales, customer service, product management, and analytics. Beyond scaling operations, upgrading to a modern support CRM will transform how you do work by breaking down departmental silos and infusing the customer voice into your business.
GenAI needs to be built-in. Not bolted-on.
It’s 2024. Saddling AI on a dated architecture just won’t cut it. Legacy systems have rigid architectures which make modifying data structures for AI time-consuming and difficult. Data silos in legacy CRMs create inconsistencies in fine-tuning. Scaling AI in a dated architecture also increases computational demand and creates performance bottlenecks.
A solution built on a modern architecture scales seamlessly for AI workloads. Retrofitting AI into legacy interfaces presents constraints in the depth and breadth of AI integration, creating a disjointed user experience and limited capabilities in extending NLP to basic functionalities. Most importantly, AI integrations create dependencies on external vendors and present challenges of lock-in and lack of flexibility. AI-native, on the other hand, promises flexibility, interoperability, and open standards.
The kill switch to app switching
SaaS sprawl brings with it a whole host of a productivity killers: app switching, data silos, endless integrations, and buggy connectors. More often than not, stitching together disparate apps feels like tossing something over a wall and hoping 🤞🏻🤞🏻 it will get caught. Ultimately, it ends up becoming a blame game of app connectors.
For every $1 spent on a legacy support CRM, organizations incur another $3 on the maintenance around it. To get your full support ecosystem up and running, you likely need:
- A fully-featured conversational chatbot that costs as much as the ticketing software
- External connectors like Zapier to create any sophisticated automations
- Middleware like Exalate to handle the sync between your support CRM and engineering work management tools such as Jira
- Tools like Fullstory and Hotjar are required to recreate issues, replay sessions, and observe engagement.
- Centralized data consolidators like Snowflake for unified reporting and analytics
- Dashboard builders like Tableau
That’s a lot of ancillary apps! If the app switching wasn't enough of a headache, the cost of implementation and administration by professional service providers shoots the total cost of ownership to the sky.
What's the solution? A unified platform with native integrations, observability, automations, workflow builders, reporting, and analytics. 10 tools to support your customers? How ‘bout just one?
Becoming a data hero
In an age of SaaS sprawl and remote work, employees are more isolated than ever - from their data and from one another. Institutional knowledge is trapped in silos, exacerbated by the distributed nature of today’s teams. Distributed teams don't necessarily mean disconnected teams. If anything, the tech stack should bring them together.
Software can be a unifying force in the modern organization. The key challenge to solve is around data fragmentation. When support, product, user, and incidents data is siloed beyond repair, how does one make sense of the data debris? IT has little time to prepare your insights. It also jeopardizes the adoption of AI. After all, GenAI is meaningless without data.
The solution? A 360° view on customers, products, user sessions, and revenue - one that all departments across an organization can access. Bringing all this information together necessitates a foundational approach, wherein each of these elements become an integral building block of the platform. AI must be built-in, not bolted on. For legacy CRMs, the opportunity to fundamentally reinvent themselves and adapt to this paradigm has passed beyond their grasp.
Less is better.
Let's face it - scaling support operations is a challenge. As usage volume grows, the need for a solution that unifies support, product, and user data only becomes more apparent. Legacy players drag you down with limited data sync, extensive custom engineering, and surface-level insights across reporting and analytics capabilities. In the face of SaaS sprawl, organizations are in dire need of a lean, clean CRM that reduces not just OpEx but also the number of tools, software subscriptions, Slack channels, and even meetings.
