AI chatbots aren’t immature technology you have to spend big budgets on for the chance to solve only painlessly executable problems. Organizations of every size use bots to answer customer questions faster, reduce support costs, and provide more consistent experiences. The right strategy will help you decide how.
Capabilities
Your AI chatbot doesn’t need to be limited to Hello World type script-to-answer actions. Chatbots are complex enough to qualify leads, walk customers through purchases, respond to common support questions, and escalate cases to human teams when necessary.
One of the biggest benefits is consistent speed. Chatbots can respond instantly and don’t need to sleep. Having a single bot manage inbound inquiries on channels that never close means your chatbot will eventually exceed human teams in service quality because it learns from repeated conversations.
Start With Strategy First
Going into a chatbot project without a clear strategy is like launching an expensive self-guided experiment. You might learn something valuable, but there will be limited business value until you run the second version.
Your strategy should outline problems you intend to solve, who you’ll serve, and what successful looks like. Consider the following:
- Identify the highest volume questions customers will ask before you decide on a solution.
- Understand if you want to use bots for support, sales, or internal productivity.
- Define quantitative goals like response time or lead conversion rate.
- Map out existing systems that will need integration.
- Identify stakeholders responsible for maintaining content, testing, and tracking metrics.
A smart strategy focuses on continuous improvement around business value, not features. It also lets you rule out vendors that don’t align with your goals so you don’t buy useless capabilities.
Objectives + Features = Strategy
Successful AI chatbot implementations pair capabilities with business objectives. Do not try to do everything at once. If your main goal is support automation, prioritize access to self-service knowledge and ticket deflection.
Sellings? Lead capture, personalized conversations, and handoff to sales reps might be more important. Your business goals should guide you toward the right features, not dictate every detail.
Where do your customers need the most help? Bots that guide users towards products can have greater impact than bots that superficially cover more topics. Provide value over variance.
Focus on Features That Matter
While many vendors provide access to similar features, not every platform excels at each function. Carefully evaluate tools that work for you versus features that sound cool.
- Does the bot understand natural language?
- Can it easily connect to your CRM, help desk, or ecommerce platform?
- Are there options to handoff conversations to a live human being?
- Can you analyze conversations to discover frequent questions and dropout points?
- Does it support channels where your customers are currently active (web, mobile, messaging apps)?
Vendor evaluation shouldn’t end when you press the go-live button. Consider how each platform enables you to refine your chatbot and automate faster as you gain more customer insights.
Build Vs. Buy
Custom bots are only necessary when you have very specific requirements or existing systems that require deep integration. Some organizations build custom bots because they can. Others do it because they must.
Buying might be the best option if you have a small to medium sized team looking for immediate value. Startups will typically choose a chatbot platform because they want to launch right away without building internal resources.
Here’s a quick comparison to help you decide between building a custom chatbot or buying an off-the-shelf solution.
| Aspect | Build | Buy | Best Fit |
| Setup Time | Long | Short | SMBs for ‘Buy’ option |
| Cost Range | High | Medium | Depends on Needs |
| Flexibility | Maximum | Limited | Enterprises for ‘Build’ |
| Scalability | Customizable | Depends on Vendor | Case-Specific |
This comparison highlights key factors to guide your decision and ensure alignment with business goals.
There is no right answer. However, if you need something up and running now buy it. If your use case is complex enough to warrant building a custom chatbot solution, establish a governance model before you begin work.
Don’t Lose Sight of the Business
Automation without intention is useless. There are several mistakes that can sabotage your ROI after the launch party.
For instance, many organizations don’t realize just how much written content is required before a bot can shine. Muddy answers and irrelevant callbacks frustrate customers and make human support agents look better.
Multivariable use cases are tempting, but Chatbots are only as good as the info queries they can access. Start small, prove your concept, then scale from there. Remember:
- Going into a project without a business objective.
- Not planning for escalations to real humans.
- Writing content too broadly.
- Ignoring your chatbot’s analytics dashboard.
- Setting and forgetting your chatbot.
The better your chatbot fits into an overarching operating model, the more time you’ll spend improving versus justifying your investment. Look for ways to automate more once you’ve fully deployed your chatbot.
Get Measuring
Look at your key metrics before deciding what you should track. If you don’t know how many questions your bot can answer without intervention, how will you know if changes you make have any impact?
Resolution rate, escalation rate, and response time are all excellent starting points. Customer satisfaction metrics are great too if your chatbot tool collects that data.
Pay close attention to the why. Why did this question come up so frequently? Why did users drop off here? Information like this can help you improve your chatbot and product. Take data from your chatbot and use it to automate quicker.
Looking for Continuing Improvement?
AI bots are never done launching. Every conversation holds the potential to surprise you and point towards marginal improvements.
Chat logs reveal real user questions. Every department should review chat logs regularly to identify areas of improvement. After all, your support team does not have visibility into messages sent via texting app or social media.
When was the last time you spoke to someone who actually enjoyed talking to a robot? Thoughtful automation respects your customers’ time and aims to reduce friction. Listen to your data and iterate often.
