AI for Customer Experience (CX)

There are many articles and podcasts discussing the pros and cons of AI use in corporations with fear and trepidation of how it could replace jobs. However, I would like to suggest another way to consider the impact of AI throughout the Customer Lifecycle Management model when strategizing on how to grow and scale a SaaS company effectively and efficiently.

AI isn’t replacing people — it’s rewriting the playbook for how SaaS companies grow. By embedding AI automation and intelligence throughout the Customer Lifecycle, companies are scaling faster and smarter — not by cutting roles, but by empowering every role to do more high value work. Instead of adding high-cost employees to take on more operational and administrative roles as the company grows, they can focus on investing in technologies with AI to help each role be more efficient and effective. This means SaaS companies can stay lean with low burn multiples extending their funding runways.

A Strategic Approach to building an AI tech stack

AI will require a thoughtful strategic design based on the corporate strategic goals. An operational plan can be established with a short-term plan to achieve some quick wins immediately and a long-term plan which incorporates a more innovative and impactful AI solution. Implementing an AI strategic plan is like implementing a complex technology stack; it takes a thoughtful design, a detailed plan, a dedicated team assigned with key sponsors at the leadership level supporting the execution. 

A more futuristic approach is for start up SaaS companies to build as much of the customer guidance and recommendations inside the product as part of the strategic product roadmap plan. Integrating AI into the product roadmap plan will ensure the product evolves with customer self-help included with every release reducing the need to build additional services outside the product. This will allow SaaS companies to hire strategic experts in specific areas for more complex customers to operationalize the technology.

What do future generations of users who were practically born using technology expect from new SaaS solutions? They are going to want to stay inside a solution to self-onboard and implement, ask questions and get answers easily and quickly WITHOUT having to go outside the solution. A good AI strategic plan is designed for the future; like a good chess game where you are thinking at least ten moves ahead. This market continues to evolve, innovate and change at warp speeds which requires SaaS companies to find innovative ways to incorporate AI into their products.

I want to share a few key learnings and thoughts to consider in building an AI Strategic plan:

1. Every company should be incorporating an AI strategy into their annual strategic plan.

2. Every employee should be encouraged to use AI daily to make their job execution more efficient and effective.

3. Utilize the best practice methodology for implementing an AI strategy to ensure it is accurate and effective for each area of the business.

4. Incorporate a plan to eliminate hallucinations for Agentic and Generative AI solutions.

5. Data quality, standardization, normalization and accuracy are required to feed any AI solution. (Garbage in; Garbage out).

6. AI is not a quick fix, but a new innovative product roadmap and operational approach that can be collaborative, creative and innovative for all.

Let’s dive into processes for each stage of the CLM where AI can impact the efficiencies of how SaaS companies operate.

AI Solution Options by CLM Stage

There are so many AI solutions on the market and coming to the market each week. I understand it may be hard to know which ones to use. Here are some guidelines for selecting some AI technologies and known solutions with new AI capabilities that are working well today:

Qualify Stage

1. Hubspot has AI capabilities that provide built-in AI assistants (Breeze), AI suggestions for workflow triggers/actions, content generation, and lead prioritization.

2. Drift provides AI chatbots that engage website visitors, qualify leads, book meetings, and routes conversations.

3. For smaller companies there are AI solutions that are newer to the market which may be a bit risky, but are lower cost options.

   1. Apollo.io provides predictive prospecting, contact & firmographic data, and engagement insights.

   2. Clay provides centralized enrichment plus intent signals. Rather than buying many separate datasets, Clay offers a unified data layer you can act on. It also provides automation of GTM workflows: triggers, segmentation, and syncs to CRMs as well as personalized outreach (drafting messages) combined with good data.

   3. NetLine is a B2B content syndication, lead generation, and buyer intent platform. It pushes content across a broad network, captures engagement, and delivers leads into the funnel of a CRM system.

   4. Alphasense provides deep intelligence to understand industry trends, competitor moves, regulatory signals, and supply chain shifts. It has generative AI support in market research helping surface insights faster. It is useful for validating markets, trends, pricing pressures, or where problems are intensifying.

   5. Atlas.ai is good when geography and location matters: e.g., for physical presence, last-mile, logistics, infrastructure, or region-specific demand. It provides market micro-segmentation understanding variation within cities, regions, and neighborhoods. It has demand forecasting and supply-demand dynamics in emerging markets or data-sparse regions.

Acquire Stage

1. Salesforce Sales Cloud w/Einstein AI uses ML models trained on your historical lead and conversion data to assign a “likelihood to convert” score to inbound new leads. Scores open deals on how likely they are to close. Highlights risk factors or deal “health” signals (e.g. lacking activity, stalled stages). Uses AI models to analyze historical pipeline, trends, deal velocity, and external factors to generate more accurate forecasts. It has tools to sequence outreach (emails, calls, tasks) directly from within Salesforce with AI assistance in what steps to include or how to schedule sequences.

   1. Agentforce provides AI agents that can engage inbound leads (as an SDR), answer questions, handle objections, schedule meetings, and hand off to Sales reps or act as a “coach” to simulate buyer conversations, conduct role-plays and provide feedback.

2.  Hubspot Sales Hub with Breeze provides similar capabilities using AI to help generate or refine sales emails, follow-up messages, subject lines, etc. It surfaces prompts, content suggestions, talking points, and prioritization for which opportunities deserve attention. It can score deals or assess deal health (likelihood to close or risk factors) based on CRM signals and behavior.

3. Alysio.ai is an AI Revenue Agent that score deals or assesses deal health (likelihood to close or risk factors) based on CRM signals and behavior. It offers the ability to ask questions like “Which deals are likely to slip?” or “What’s my forecast coverage?” and get answers based on unified data. It can act (e.g. update opportunity fields, schedule tasks, enrich contacts) from the same interface. It integrates data from CRM, engagement tools, marketing, CS, etc., so insights are cross-tool and contextual. You can tell Alysio what automations you want (e.g. “Send me alert when pipeline < 3× target”) and it builds them, skipping manual workflow creation. It supports Salesloft integration as well.

Implement Stage

1. Rocketlane provides the ability to create an automated onboarding process from welcome letter to providing access to software and a workflow to getting started including AI capabilities.

2. GuideCX, Wrike or Workfront work management solutions provide the ability to create a standardized customer roadmap or implementation plan to guide customers through the process to operationalize the software. Some integrations may be required to automate the process to create plans from the sales close and provide live updates back to the CRM.

3. Zendesk (AI + Advanced AI + Generative Search), or Freshdesk (Freddy AI) streamline the management of support tickets, knowledge base and online self-help centers. With additional AI capabilities, AI agents (trained by accurate content and question and answer data) can help customer support scale, achieve consistent response times and the ability to provide 24/7 support in the early stages.

4. Gainsight + Skilljar + Staircase + Atlas can provide a comprehensive platform for managing education content and delivery, managing renewals, prioritizing customers based on health-score, expansion opportunities, renewal dates and product engagement and indispensability usage.

5. Whale or Notion AI provides knowledge playbook generation. These can store and update your Customer ROI Playbooks including how to demonstrate value for each persona or use case. These can be auto-generated and updated by AI using customer data and templates.

Value Stage

1. Gainsight, Churnzero or Strikedeck customer management solutions are the better solutions for monitoring and tracking customer results utilizing health scores based on product usage stats, progress to current strategic plans, expansion opportunities and contract renewal management. Gainsight and Churnzero are incorporating some AI capabilities to improve the automation of common CSM tasks and activities.

2. ChatAID provides conversational engagement and content automation and can auto-generate customer-facing updates — i.e., personalized release notes, “What’s new” digests, and value-based summaries. Integrate it with CRM or CS data to answer customer questions like: “How much value did we realize this quarter?” It can also summarize your QBR decks into conversational explanations.

3. Revio provides customer feedback and revenue intelligence. Revio’s AI can parse customer sentiment, usage, and feedback from multiple sources (emails, NPS, tickets). Use it to identify risk vs opportunity signals and trigger automations: e.g. when a customer gives high feedback, auto-create a “Success Story draft” workflow.

4. Gamma provides AI visual storytelling and deck creation. Ideal for ROI & QBR decks. Feed it usage, KPI, and value metrics from the CS system or data warehouse, and Gamma will generate executive-ready decks showing ROI, adoption, and business outcomes. It can create branded templates for QBR format. Gamma will update the visuals automatically with new data.

5. Zapier provides workflow automation (no-code, B2B SaaS). Connect all your systems: CRM (HubSpot/Salesforce) → Support (Zendesk/Freshdesk) → Education (Skilljar/Docebo) → Email (HubSpot/Mailchimp). Use it to trigger customer communications automatically when new features, milestones, or value thresholds are met. Example: when usage hits 80% of license value, trigger a “ROI milestone” email with customer success metrics.

6. n8n.io provides advanced workflow & API automation (open source, more flexible than Zapier). Use it to automate cross-system data collection and orchestration for deeper use cases. Example: pull product usage data from a SaaS DB → aggregate it with CRM + support data → push summary to ChatAID for generating a “Value Summary” message → send deck to Gamma → trigger an internal alert for CSM to schedule a review.

Renew and Expand Stage

1. Narrato.ai or Tome.app provide AI content creation and narrative generation. These can be used to draft ROI stories, use-case documentation, or renewal justification one-pagers. Pull real data from Gainsight and CRM and let the AI build the narrative and supporting visuals.

2. Amplitude + Pendo + Mixpanel provides product analytics and journey tracking. This combination can use product usage metrics to prove ROI in quantifiable terms: “Customer automated X workflows which saved Y hours/month and generated $Z impact.”

3. Gainsight or Planhat provide AI-driven health scoring, value tracking, and renewal forecasting. Gainsight is more comprehensive and good for all markets including Enterprise. Planhat is flexible and easy to use but better suited for SMB and MM. These solutions connect product telemetry + support + CRM to auto-generate health scores and ROI metrics. These tools help define and track Customer Business Outcomes (CBOs) like adoption, retention, or efficiency gains.

4. Hubspot Catalyst provides expansion forecasting, success metrics, and CSM dashboards with predictive AI insights. Built for small CS teams, it is native to HubSpot with Salesforce integrations.

5. Pendo Free / Amplitude Growth provides product analytics, AI adoption scoring, and trend detection. It can detect where users hit adoption ceilings or engage with premium features and exploit customers with potential for expansion.

Costs Aligned to SaaS Growth Stage

AI Stack examples based on SaaS company size

For start-up SaaS companies creating a “lightweight Gainsight” using Planhat + n8n + Gamma will support capturing data, scoring readiness, and value storytelling without enterprise overhead and will be at a lower price point. This stack could be perfect for startups proving ROI and renewal cases fast. Start-ups can add a lightweight work management solution like Guide CX or Wrike that has a low cost to start and can expand as your customer base grows. Adding work management data to your Agentic AI will provide more intel to act more accurately.

For Mid-Market SaaS companies, they can form an AI-driven “Expansion Radar” using Totango with Pendo, automating which customers are trending upward and syncing that to renewal plans. Adding Visible.vc or Gamma to the stack will provide value storytelling. This stack is ideal for Mid-Market SaaS aiming to scale renewals and expansion via more robust data.

For larger Enterprise SaaS companies using Gainsight with Clari or Gong and Amplitude, this stack will bring true predictive Customer Growth Intelligence — combining usage, engagement, CRM, and revenue to forecast expansion and automatically build the business case. There are a few other solutions that can be integrated to provide additional insights at this level. For example, integrating a work management solution to provide implementation progress stats can enhance the customer health score and provide AI with additional insights on expansion opportunities as the customer completes the first Phase and is ready to start the next Phase of their implementation, thus expanding their use of the solution. This tech stack can be effective for large SaaS firms managing $50M+ ARR.

With all this information on various AI strategies, there is one large issue that still needs to be addressed in every Agentic AI or Generative AI solution and that is Hallucinations. This is why I stressed at the top of this article the importance of creating an AI strategic plan. If these basic technology stacks allow too many hallucinations, then employees and customers will quickly lose faith in the information provided or accuracy of the actions being automated. It is important to incorporate a process for reducing and eventually eliminating hallucinations in any Agentic AI or Generative AI solutions.

This may lead to a custom solution with companies like Nice CX or Wallabi where they create custom Agentic AI or Generative AI solutions with more complex algorithms for testing and eliminated all hallucinations, providing a much more robust and accurate AI solution. In most cases, the cost savings are associated with the AI solution automating, accelerating and scaling many tasks, activities and processes that would require additional headcount to execute daily, weekly and monthly. These are worth considering, even for start-up companies, as they can provide highly effective and accurate Agentic AI solutions that extend the funding runway due to enabling a leaner, smaller team to be more productive. This approach can extend the need to hire additional headcount until the capacity plan proves they are required by achieving the revenue and customer growth targets. It could also change the corporate organizational structure to utilizing more high value roles with a smaller team.