Adding conversational marketing to a website user experience opens new opportunities for marketing and sales teams. At PFL, we recently implemented Drift for chat and conversational marketing. Our team is hard at work building and optimizing playbooks for maximum prospect engagement.
We began exploring chat integration to capture website visitors’ attention and deliver value more quickly. We needed a tool that would allow us to customize a user’s experience based on profile information stored in our CRM. User analytics and reporting were also key factors in our buying decision. Our chat integration needed to reveal opportunities for on-site engagement, but also inform other areas of our multi-channel marketing efforts.
Our approach has been to launch quickly and iterate often. We’re seeing some great early success. To share some of our key findings, I asked Ernie Mudis, Director of Marketing Ops, and Geoff Freeman, Inbound Sales Development Representative, about their experiences with implementing and executing Drift.
Why did PFL implement a chatbot?
PFL was looking for a way to engage site visitors at a higher level. A chatbot, also known as conversational marketing, is a great way to guide people to content that may be of interest to them. We wanted to better “meet our prospects where they are,” as I like to say. The faster we can direct visitors to the content experience they want — whether that’s a page on our website or a conversation with one of our reps — the faster we can provide value.
We selected Drift software for their like-minded approach to account-based marketing (ABM) and their strong feature set.
What are PFL’s business goals for this chatbot implementation?
The overarching goal is very simple — create more meetings between the right prospects and our sales team. That takes two steps. First, if we don’t recognize the site visitor through our integrations, the chatbot needs to find out who the visitor is and, hopefully, get their contact info. Second, the chatbot attempts to engage people who fit our ideal customer profile (ICP) in a conversation, whether that’s with a live sales rep engaging them through chat, or in a scheduled meeting.
We’re looking at this not just as lead generation but as lead interaction. Often, we have already identified that the person visiting the site is a prospect, and because we have those details in our CRM, we’re able to offer up a chatbot playbook targeted to the individual.
How does the chatbot integrate with other PFL systems?
The most essential integration is with our CRM, Salesforce. Salesforce is our source of truth and it contains a large body of completed research on our target accounts. Our profile data allows us to know who does and does not fit our ICP. It helps us know which playbook to offer a site visitor.
How does this chatbot affect Inbound Sales, and how are Marketing Ops and Inbound Sales working together?
A big part of what Geoff does as our inbound sales rep is triage, basically using whatever information he has about a contact to determine how to handle their engagement. With this chatbot, we’re taking some of Geoff’s processes and automating them, freeing him up to focus on holding those personal conversations. It also allows Geoff to more easily identify and focus on high-priority prospects.
Even though these are early days, there are three things I’ve noticed. First, the chatbot brings in leads. We normally would have missed these leads because they were looking for a particular area of our business and couldn’t easily find it.
Second, I’m using Drift’s integrations with Demandbase and Salesforce to leverage intent data. For example, say I have someone in an outreach sequence — Drift can tell me when that person is on our site and engaging with the content I’ve sent. That lets me either jump in and start a conversation in Drift, or I can see what they’ve been looking at and use that knowledge to better personalize the next message to them. That’s already driving better conversations with customers.
Finally, I’m using the prospecting tool within Drift to review the people who have been on our site against our outbound or prospecting lists. With that knowledge, I can drive people to the next stage in the sales funnel.
How long did the implementation take and what early successes have you seen?
The initial implementation took about three to four weeks. We decided that we wanted to move quickly to build basic functions so we could get up and running. By launching sooner, we could iterate earlier and gather intel about how users were interacting with the playbooks. Currently we’re running on two-week cycles to monitor, measure, and improve.
What challenges did you encounter during the implementation?
The ongoing challenge is figuring out the best way to hook someone in a conversation. We want to be engaging, get to the point, and keep our playbooks fresh and current.
There’s also the challenge of being direct without being off-putting. As we identify people who are ICP, we don’t want to close doors on other people who may have a need for us even though they aren’t an obvious fit. We’re optimizing for people who need our martech solutions.
The initial challenge for me was steering how the chatbot sent leads to me. When we first turned it on, we were a little too strict, so I wasn’t getting any conversations at all. Then we tuned it too far the other way, and I had too many connections with people who weren’t a good fit. It was a matter of figuring out the right questions for the chatbot to ask.
What plans do you have for expanding conversational marketing?
We want to get more reps added so we can offer more live conversations, as well as starting to use campaign-based triggers. We also have a wealth of opportunity to start offering more logical, related content to visitors based on data, which will boost a variety of site metrics.
We’re going to continue making it easier for prospects to engage with us incrementally while also accelerating their journeys.
As someone who’s using the tools, I see us getting to the point where the chatbot can drive visitors to preferred address landing pages so we can send direct mail. Or, because the chatbot conversations get added to Salesforce, we can set rules to trigger sending a package automatically based on the length of their engagement with the chatbot. That helps drive prospects to the next point in the conversation.