Close a PoC with a large enterprise within 3 months
An NLP chatbot company has raised funding and is ready to grow. The tech company identified auto insurance as the industry to target, and they hired a lead generation agency. Their chatbot solution has unique enterprise features. Therefore, it can be considered a new technology category. The company targeted technical buyers across the auto insurance industry such as VP of Technology, ML Engineer, Data Scientist, Director of Software, etc. They could not find any relevant person in the targeted account, and the lead generation agency worked with Enki to deliver the results.
Challenge
Traditional Contact Databases with pre-selected job titles are not enough to discover modern buyer groups. Job Titles and responsibilities are not the same things in large enterprises. Therefore, job titles don’t provide any clues on the current projects or initiatives these buyers are working on. Second, the industry categories are too general. They often provide too many or too few results that may not be relevant.
Unlike traditional outbound marketing funnel such as list building, mass emailing, tracking, scoring, phone calls, Enki uses ABM principles and starts with identification.
Our client wants to understand:
- Do auto insurance companies such as AAA have any initiatives in Chatbots?
- If they have, what are their opinion on the technology?
- Who are the decision-makers related to Chatbots?
- How can we start engaging with them?
Solution
Our client entered their account name, AAA, with Solution Attributes to Enki. Since our client develops a Chatbot application, they want to gather all the insights about Artificial Intelligence, NLP, and Chatbot.
Besides, their solution improves Customer Experience, reduces Call Center Volume. Therefore, they want to know whether the target account has any insights or initiatives on them.
Solution Attributes helps us differentiate our products. For example, there could be two different Chatbot applications that may focus on two different markets. For example, one company may focus on improving Emergency Roadside Assistance, and the other may focus on Saving time in deploying Chatbots. With Enki, we can gather insights based on the different value propositions.
Figure 1: Solution Attribute could be the Value Proposition or Pain Points you address. Enki will generate insights based on your solution attributes, and this will help you be more relevant to your target company or industry.
Figure 2: Heat Map provides trendy topics that our Target Company talks about. Tailoring our value proposition to Heat Map topics could increase the conversation rate. In addition, comparing various Heat Maps within the peers could give us an idea of which Solution Attributes are more important for certain companies.
AAA focuses on Roadside Assistance, Emergency Roadside, Customer Experience. They also have a few Chatbot initiatives. Let’s dig in further.
Does AAA have any Strategic Initiatives in Chatbots?
As shown in the video, AAA is developing its Chatbot application, and Laurie Sadow is leading this initiative. Pay attention to her title, head of User Experience for eBusiness. There is no mention of NLP, Data Scientist, VP of Engineering in the title. That explains why our client could not find any leads initially.
What are they talking about Chatbots?
Besides, Enki finds AAA reduces costs with AI-Powered Sell-Service under Challenges and Pain Points. Enki can discover your target account’s challenges, issues, solutions based on what’s published on the web. We can compare various Target Account’s Pain Points to personalize our message.
Enki also discovers “AAA was struggling to support their members with emergency roadside assistance”. And “Unpredictable weather made it a challenge to staff their contact center properly as winter storms would create a sudden spike in calls or chats from stranded motorists.” These are great insights to use in our messaging.
Who are the Decision-Makers related to Chatbots?
Enki discoveries the job titles to target that they haven’t thought of before. For example, Enki discovers Mark Pelletier, VP of Digital Business, talking about how members drive the digital experience. As we can see, Mark never mentions Chatbots, but Enki is smart enough to find associations between Chatbots and Digital Experiences. Enki finds overall 50 top prospects related to digital experiences, road assistance programs, and chatbots. We can export the list with their emails and phone numbers and import our CRM system.
How can we start engaging with them?
Enki prepares personalized emails to send the Key Decision Makers. Besides, we captured their Pain Points, Strategic Initiatives, Partnerships, Executive Insights, etc. These could help us to run marketing campaigns. Their talking points are the best way to break the ice when emailing and talking to our prospects. This will show that we have done our homework and build trust and rapport with the Key Decision Makers and Champions.
Value Proposition
Without Enki, they were not able to find any relevant people in AAA. Enki discovered a new customer and market for them. With Enki, our client signed a PoC within 3 months.
Summary
Enki completed this project within 2 hours by:
- Searching 1.8 billion websites
- Finding 5688 relevant articles
- Reading 12,308,352 words
- Extracting 760 most relevant paragraphs
Our client got 355 hours’ worth of search, saved 2 FTEs for a week, AND shorten their sales cycle 3X compared to other accounts.
Discover
prospect strategic initiatives based on your value proposition
Find
the most relevant decision-makers based on your unique product
Uncover
the company executive's opinion of your industry
Generate
personalized message to start a conversation
Now, how can we repeat this success? How can we find more lookalike accounts and decision-makers? And what happened to the lead generation agency?