Arnav is the Director of Content Marketing at Tars, a chatbot software solution that uses conversational landing pages to engage and convert ad-click prospects.
When Facebook released its chatbot platform in 2016, many in the tech world thought that bots would be the next frontier of human-computer interaction. However, as time has passed and the hype around Messenger bots has died down, it has become increasingly clear that bots are not going to supplant apps as the primary way individuals use the internet any time soon. That said, chatbots have found a promising niche in digital marketing. Increasingly, marketers have found that the killer app for chatbots is conversion rate optimization.
Chatbot marketing offers the promise of a more engaging lead generation and qualification process. Of course, to actually see any of these benefits you need to know how to approach the technology for the first time.
As someone who has worked in the chatbot space for the last three years, I have found that many businesses have a misguided notion of how chatbots are going to help them, resulting in a subpar chatbot that fails to meet their and their prospects’ expectations. Don’t fall into a similar trap. Learn how chatbots can actually help you boost your conversion rate and achieve the marketing holy grail: a lower CPA.
A Chatbot is not a Chatbot
To understand how a chatbot can help you reach your PPC goals you need first to deconstruct your preconceived idea of what a chatbot is. Most people define a chatbot (especially in the context of business) like this:
“‘A computer program designed to simulate conversation with human users’ to facilitate a trade of information or services.”
While such a definition is technically correct, it is not the right way to look at chatbots as a PPC marketer. The definition above sets the benchmark for a chatbot’s capabilities at human-level intelligence. When applied to PPC marketing, this benchmark generally manifests itself as an expectation that chatbots will serve as highly intelligent sales or customer service reps who live on your PPC landing pages and can guide prospects through the buying journey.
This expectation is certainly novel but it is unrealistic. Artificial Intelligence (AI) will undoubtedly play an increasingly important role in the way PPC marketing campaigns are run in the future, but:
Unless you are Google, Facebook, or Amazon, there is little chance that your chatbot will be able to understand human language well enough to handle every query users send its way.
This will inevitably leave both you and your prospects disappointed when the bot gives a nonsensical answer to a reasonable query.
Chatbots are Conversational Forms
So if chatbots aren’t the ultra-intelligent beings that we were promised then how are they going to drop your cost per acquisition? The key to answering this question is to set a more manageable benchmark: the humble lead capture form. Think of chatbots not as hyper-intelligent sales agents, but rather as conversational forms. If you task a chatbot with collecting the same details as a lead capture form, it does not require AI, so it will not fail to meet expectations and might actually exceed them.
Lead capture forms are not hard to beat. They are fairly dull and no one likes filling them out. The back-and-forth, two-way nature of a chat (even if it is with a dumb, AI-free bot), is a far more interactive way to capture the same information a form does. Prospects are given a constant stream of instant feedback for each of the details they send which is reminiscent of the gratification that their favorite apps give them every day.
The end result is a more engaging lead capture experience which leads to a higher conversion rate. This, in turn, drops cost-per-lead (by half in many cases) which in turn drops CPA.
Where's the proof?
I have tried this approach with several of my clients’ ad campaigns and have seen an increase in conversion rate by as much as 200%. But, my favorite demonstration of the effectiveness of this approach doesn't come from the marketing space.
I am a big fan of the DoNotPay app which lets you sue people with the tap of a button. When it began, DoNotPay was a chatbot that helped aggrieved citizens draft short letters to contest parking tickets. Joshua Browder, the bot’s creator, recognized that the contestation letters were formulaic, requiring the same set of details for every citizen.
His bot asked for each of these details individually in a conversational manner. As you might imagine, the bot didn’t require highly advanced AI to accept the details (e.g. you don’t need too much AI to pull a name from the phrase “My name is Arnav Patel” or to pull an address from “I got the ticket at 12345 Clover Blvd”). After collecting these details, the bot could compose a short letter by plugging details into a template the citizen could send to their local government. The bot did not have to use any fancy underlying tech and performed more like a conversational form than a robot lawyer.
This approach was so effective that DoNotPay helped squash over 200,000 tickets over the months following its release. This process of essentially tricking users into filling out a form is the same approach to chatbots that I described above.
The key to building an effective chatbot strategy is managing expectations. If you try to recreate a conversational agent with the intelligence of Jarvis from Iron Man you will inevitably fail. Both you and your prospects will be disappointed when the bot doesn't perform as promised. If you set a more manageable goal and make a bot that improves your lead capture experience, your prospects will feel more engaged and you will convert more leads with the same ad spend.
This thought process affects your bot’s goal and how you phrase the bot’s conversational flow. I would recommend creating bots which have a very fixed and narrow objective (e.g. capturing a lead for a particular product/service) and phrasing questions with a similar fixed objective as one might do with a form field (e.g. ask “would you like help with X or Y” instead of a more open-ended “how can I help you?”).
Using this approach allows you as a marketer to feel the benefits of a chatbot’s engagement without the fear of awkward examples of failing AI that alienate prospects. The end result is a higher conversion rate, lower CPA, and a more efficient PPC campaign
About Arnav Patel: Arnav is the Director of Content Marketing at Tars, a chatbot software solution that uses conversational landing pages to engage and convert ad-click prospects at a higher rate than traditional static landing pages. Arnav builds chatbots and frequently writes about conversational design on the Tars blog.