The traditional wisdom has always suggested that in order to build a lead database, it’s vital to ask for the visitor’s email address right away upon entry into your website. The facts are now showing that asking the customer to provide contact details at the very beginning of a conversation has a devastating effect on your completion rates before you even start a conversation.
This article details the gross discrepancy between what software vendors advertise and the realities of how these systems work when put into practice. We will also expose the loopholes of the old theories surrounding automated capture and discuss precisely which chatbots for lead generation will convert your silent internet traffic into qualified sales appointments.
The Actual Economics of Chatbots for Lead Generation
One harsh reality is that most organizations are treating chat products as regular web-based forms that have been reduced in functionality and tucked into a small pop-up window. The conversion rates for web-based forms have fallen significantly, with an average of less than 3% of leads being converted through web-based forms.
On the other hand, if constructed correctly, conversational capture technology can provide a conversion rate anywhere between 15% and 25%. The critical difference between the two numbers is the integrity of the logic supporting the conversational capture technology.
The fact is that if you ask the customer for an email address as part of your initial interaction, the customer will either immediately leave your website or will continue down the path of answering questions, but you will lose 60% of the customers who have answered three or more questions without receiving any value in return.
The use of auto-open messaging functionality the second your visitors hit your website increases your website bounce rate by an additional 18%.
The data illustrates the breakdown points of traditional systems:
Approximately 22% of all captured leads are lost because there is no direct contact between the lead and a sales representative.
Approximately 32% of leads that are highly interested will not provide any information until they receive an immediate transfer from the chat box to a live human representative after completing the qualifying process.
49% of calls made using external tools such as ChatGPT are highly qualified, indicating that these types of systems are capable of supporting AI-driven intent.
Analyzing the Market: Top 12 Chatbots for Lead Generation
1. Drift
Built specifically for enterprise account-based marketing, Drift continues to be the safest bet for large sales organizations.
For example, when Wrike implemented Drift's AI technology, they experienced a 496% YOY increase in pipeline contribution. Drift is also the most expensive of these options, but the connection to Salesforce is deep and direct.
2. Qualified
Qualified is a direct alternative to Drift and therefore has a strong connection to the Salesforce ecosystem. Qualified's primary strength is in providing real-time alerts whenever a target account visits their site.
AdRoll switched from using Drift to Qualified and saw a 128% increase in marketing-qualified leads and a $7.2M influence on the pipeline.
3. Intercom
Intercom is the leading chat platform in the mid-market software market. Recently, Intercom shifted the market by charging $0.99 per resolution via their Fin AI model.
This changed how companies budget for marketing because now companies can pay as they use. Currently, Intercom's Fin AI model resolves 69% of standard customer inquiries without human intervention.
4. Tidio
Tidio is the go-to chat platform for small businesses and e-commerce sites.
Their Lyro AI model allows the platform to effectively manage traffic spikes and respond to repetitive inquiries, resolving an average of 67% of all inquiries. Unlike most other enterprise platforms, which require contacting them via phone to find out the true cost of use, Tidio publishes all costs and pricing publicly.
5. Landbot
Landbot has a very useful visual building tool that helps teams with minimal technical expertise create functional chatbots for lead generation.
6. HubSpot Chatbot
HubSpot is a suitable option for users of HubSpot as their core customer database.
The HubSpot Chatbot does not have the advanced AI capabilities of other enterprise-level systems; however, since it is natively integrated into HubSpot, it will have superior mapping of contact records compared to other systems, as it is native within HubSpot.
7. FwdSlash
FwdSlash is the ideal fit if you are a mid-sized software team looking for an intent-driven conversational flow builder that allows teams to build customized, intent-driven conversation flows but are unable to afford the very high costs associated with many legacy systems.
8. TailorTalk
Speed is a factor when launching new software. With TailorTalk’s extremely fast setup time, marketing teams can build and launch a working system in 30 minutes.
This has allowed for rapid testing of campaigns and the ability to run campaigns with a very short lead time.
9. Botpress
Botpress has been built for teams looking for greater control over how their conversational AI operates.
The Botpress platform allows developers the ability to create their own individual models and train them on how to respond to more complicated questions about products, based on their company’s existing documentation.
10. Manychat
Manychat is, by far, the leader in social media platforms, especially with direct-to-consumer brands and influencers.
Manychat captures leads from direct messages sent via Instagram and WhatsApp and provides a private sales channel, allowing conversations to be moved from a public comment to a direct message system and have a lead capture capability.
11. Zendesk
While Zendesk is mostly known as customer support software, their ability to capture leads with their large ecosystem is very strong.
Companies that prefer to keep their sales and support chat as one integrated system are the most secure option.
12. Typebot
Typebot, a tool to create an experience similar to a chat interface, allows teams to create qualification steps with an open-source framework, so the chat experience is as organic as having a natural conversation while still collecting data in a neat and tidy manner like a standard web form.
Creating Effective Qualification Scripts
If the company's sales process is ineffective, it will not matter which software is used. Many companies are not able to achieve success through chatbots for lead generation because they are not mapping well-known sales methodologies (such as BANT and MEDDIC) into the automated chat flow.
For example, NCR/Patterson has been able to develop a very effective qualification flow, creating $1.5M worth of pipeline within 11 weeks, by achieving an average response time of 25 seconds. In lead generation today, speed is everything.
Additionally, if a visitor is indicated to have a low budget in the chat flow, it is important to immediately provide a link to a free guide. Similarly, if a visitor indicates that they have less than 30 days to make a decision, the chat flow must provide an immediate link to book a meeting on the calendar.
When designing a chat flow, be careful to avoid these major errors:
In the first message, do not request the visitor's email address.
Failing to match the data fields in the chat flow with the exact data fields in the CRM.
Do not leave the visitor without a clear path to escalate the chat flow to a human agent.
The Truth About Conversational Capture
The shift in the marketplace from old-style static "Contact" pages will continue to increase. Software alone cannot generate revenue. Instead, businesses that experience consistent success will view automated chat as a method of filtering qualified prospects from the pool of non-qualified prospects rather than as a general net.
The most successful companies will be utilizing the same processes and systems as all other businesses. In addition to mapping each step of their qualifying process, they track each question that their automated chat is asking and the number of prospects who leave (or drop off) after each question or step.
Because their sales teams can jump into a live chat session within a split second, they will be able to maximize their utilization of the available data to convert a greater percentage of prospects into customers. As such, choose your chat system based on the integration of your current database as well as your ability to provide a live handoff, rather than base your decision on a vendor's marketing materials.
Common Questions About Conversational Chatbots
How does resolution-based pricing for automated chat impact marketing dollars?
Most systems charge for providing a resolution based on a certain amount of time, such as Intercom, which charges $0.99 per resolution. This business model forces teams to have to be extremely focused on the optimization of their automated answers.
If your chatbots for lead generation cannot handle general or vague traffic effectively, your monthly expenditures will be unpredictable and may escalate significantly. Therefore, it is critical that you are monitoring your cost per engaged lead in order to stay on budget.
How do I effectively measure conversion rates from automated chat?
When measuring conversion rates, it is important to not focus only on total website visits as your baseline for metrics. Instead, the initial baseline should be on your engagement rate. Once you determine your engagement rate, you must then calculate your conversion rate based on the number of engaged users who utilize the automated chat and ultimately complete the qualification process.
The true standard set for every company that utilizes automated chat is to achieve a completion rate between 25% to 40% of engaged users.
How does CRM field mapping create opportunities for lead drop-off?
The likelihood of a prospect dropping off once he enters an engaged state into your automated chat is extremely high if the custom variables in your automation chat flow do not match the exact text fields of Salesforce or HubSpot.
If the information breaks during the handoff from the automated chat to the sales representative, the sales representative will be unable to gain the proper context from the information that was captured during the conversation with the prospect. Without this context, there is an extremely high likelihood that the representative will ask the prospect questions that he has already answered, which could create an obstacle in the deal-closing process.
Why have multi-agent systems begun to replace traditional 'single-agent' systems?
Traditional chat systems utilize logic trees to capture users' intents. Therefore, the information contained in these trees is far too rigid for the modern buyer. As a result, multi-agent systems utilize separate underwriting models to complete different tasks.
For example, one model captures the initial intent of the user, a second model works in the background to collect additional information to enhance the existing dataset, and a third agent schedules users for an appointment. Using multiple models creates a significantly more frictionless experience when dealing with higher-value prospects.