Lead generation is one of the six1 most important metrics for measuring the effectiveness of marketing campaigns. However, the subprocesses within a lead generation strategy, such as reaching your target audience or gaining/keeping new followers, are a challenge for %632 of the marketers.
To mitigate such challenges, companies can use a lead generation chatbot to:
- Better qualify leads
- Identify potential customers
- Improve their marketing efforts, among other benefits.
This article explains what lead generation chatbots are and their top 8 benefits.
What is a lead generation chatbot?
Lead generation bots are a type of conversational AI chatbot designed specifically to navigate the customer through the sales funnel. In order to improve lead generation and sales efforts, these chatbots can:
- Initiate interactions with potential leads
- Ask relevant questions
- Qualify leads
- Collect contact information
- Nurture them
- Transfer exceptional cases to a human agent
- Send the data to a CRM system to be used by the sales team.
Moreover, lead generation chatbots, like other chatbots, can be deployed on various platforms like websites, social media, and messaging apps for optimum accessibility.
1. 24/7 availability
Constant availability is a benefit of all chatbots. By being available 24/7, a lead generation chatbot can immediately respond to potential customers and nurture customer relationships to get more qualified leads anytime of the day.
A study done by HBR showed3 that an equal number of companies were likely to answer a customer’s question in 5 minutes, 24 hours, or never. But companies that answered a customer’s question within the first hour were x7 more likely to qualify leads than those doing so after an hour, and x60 more likely than those doing so after 24 hours.
So companies should take advantage of chatbots for qualifying leads as they offer instant and personalized responses.
2. Instant lead qualification
Lead generation bots let companies instantly auto-qualify leads by:
- Asking a series of predefined questions about a product/service
- Comparing customers’ answers to the knowledge-base to determine if they qualify as high-intent leads
3. Scalable lead qualification
By using a lead generation chatbot, companies can screen more website visitors and identify more leads without increasing customer service teams’ workload.
3. Automated data collection
Chatbots can automate the data collection from target customers, a process otherwise done manually from lead generation forms. Data of interest would include:
- Contact details
- Demographic information
- Company info (for B2B sales)
- Purchase intent and preferences (asked directly or captured from product pages they visited)
- Pain point or needs
- Source of the lead (where the lead came from)
Furthermore, once all the useful data of customer journey and the high-quality leads are collected, the chatbot can automatically transfer the information to the CRM software for a consolidated holding of customer data.
4. Personalized interactions with potential customers
The captured data can be fed into the personalization algorithm of a chatbot for a personalized interaction with the lead. For example, if:
- The quality leads show interest in a certain product, the chatbot can nurture them by suggesting similar products
- The cart is abandoned, the bot can send the customer a reminder
- The business has different teams for different product lines or regions, the chatbot can route the lead to the right team
- A site visitor needs help during the sales process, the chatbot can guide
- The tone of two customers isn’t the same (i.e., one is optimistic and the other confused), chatbots with generative AI technologies can adjust the conversation tone to sympathize with the customer
5. Enhanced customer engagement
Perhaps the most important benefit of chatbots for lead generation is their ability to:
- Instantly answer current and potential customers’ questions
- Offer human-like responses
- Navigate them through the sales process
The overall effect would be an intensified and active user engagement, which could lead to customer conversations and to higher conversion rate.
6. Omnichannel presence
The omnichannel presence of a chatbot can improve lead generation by interacting with high-quality leads across websites, social media platforms, messaging apps, etc. This can enhance customer experience, improve customer satisfaction and brand visibility, and increase the possibility of capturing more quality leads.
7. Reduced costs
The culmination of all the aforementioned benefits of using chatbots in the lead generation process increases operational efficiency and lowers costs. That’s because whilst the bot is collecting lead information and answering customer questions round-the-clock, the sales and customer service teams can dedicate more time to value-driven tasks.
In addition, deploying chatbots for lead generation, especially as the company’s operations grow in size, is more economical than generating leads by hiring additional employees.
8. Detailed analytics
Lead generation chatbots can offer a wealth of useful analytical data, which would have been difficult and time-consuming to capture manually, to be used in marketing campaigns. Metrics include, but aren’t limited to:
- Total interactions: Counts the total number of interactions the chatbot has had.
- Engagement rate: Proportion of users who interact with the chatbot after it initiates a conversation or sends a prompt.
- Qualified leads generated: How many users the chatbot has qualified as potential leads based on their responses to its questions.
- Conversion rate: Proportion of users who become leads or customers after interacting with the chatbot.
- Response time: Measures the time it takes the chatbot to respond to user queries.
- Session duration: Tracks the average length of user interactions with the chatbot.
- Drop-off points: Tracks where in the conversation users tend to drop off or stop interacting with the chatbot.
- Customer satisfaction: If you program your chatbot to solicit user feedback, the data gives a sense of how users perceive their interactions with the chatbot.
- Top user queries: Analyzing the most common questions or commands given to the chatbot can provide insights into what users are most interested in or confused about.
- User demographics: If the chatbot collects users’ demographic data consensually, it can provide insights into the market segments that you’re reaching.
For more on chatbots and marketing
To learn more about how chatbots are being used in marketing efforts, read:
- Chatbot Marketing: Boost Customer Interaction & Sales
- Conversational Commerce: Benefits & Best Practices
If you are ready to invest in a conversational AI solution, visit our data-driven list of chatbot providers.
And if you had any more questions, reach out to us:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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