How a SaaS Marketing Team Reduced Time to Opportunity to Just 3 Days

LSports redesigned their inbound motion around real-time AI conversations. Here’s what other B2B teams can learn.

B2B buyers have changed how they evaluate products.

With AI tools making research faster and more detailed, many buyers now arrive on a company’s website already knowing what they’re looking for. They’ve compared vendors, explored documentation, and narrowed their options before ever speaking to sales.

LSports, a global sports data provider serving tier-one and tier-two sportsbook operators, began seeing this shift clearly. Buyers weren’t coming to the site to begin research. They were arriving with intent and eager to move forward, but their inbound process hadn’t caught up.

Most B2B sales teams still rely on a familiar system: forms that collect lead details, route them through scoring models, and eventually trigger follow-up from an SDR. LSports still uses forms too. The difference is that forms are no longer the primary path for buyers who already know what they want.

The debate around those forms usually sounds like this: fewer fields mean lower friction but worse qualification. More fields mean better qualification but lower conversion. So teams split the difference, debate field order for weeks, and call it inbound optimization.

LSports had spent time in that loop as well. With roughly 40 inbound leads per day, marketing was scoring them in HubSpot before routing to Salesforce, where regional SDRs would follow up.

The system worked. But “works” and “fast enough” are two different things in a market where latency is everything.

In sports betting data, low latency is the product. It determines whether an operator can offer competitive live odds before prices shift. When your entire value proposition is speed, having high-intent buyers submit a form and wait two days for a demo booking is a poor way to make a first impression.

LSports decided to redesign the inbound experience around one question: How do you engage high-intent buyers while their intent is still active?

High-Intent Buyers Don’t Wait

High-intent buyers don’t behave like everyone else in your funnel. They’re not casually browsing. They’ve done their research. They know what they need. By the time they reach your website, many have already decided they want your product, and the only real variable is how long it takes you to catch up.

Alon Kivity, Head of Digital Marketing at LSports, put it plainly: “If someone is ready and you answer in a few days, you lose the moment.”

That moment isn’t a metaphor. It’s a literal window where a buyer’s intent is active, their calendar is open, and their attention hasn’t been claimed by a competitor. Forms, qualification queues, and asynchronous follow-up sequences are designed to manage volume. They’re useful for many inbound scenarios, but they’re not ideal for buyers who already know what they want.

The counterintuitive move is recognizing that not every inbound buyer needs the same process. The high-intent cohort needs a completely different path, and that path should be frictionless.

Replacing Forms Wasn’t the Real Change

LSports introduced conversational AI through Knock alongside their existing forms. The goal wasn’t to eliminate forms, but to create a faster path for buyers who already know what they want. The shift sounds simple. The GTM restructuring behind it was not.

Adding a chat interface isn’t a strategy. What made the difference was building the AI into the actual qualification and routing logic, not bolting it on top of an existing process.

Three structural changes made the shift possible:

1. Rebuild lead scoring around conversation signals. LSports already tracked buyer behavior across ads, email, and web activity. Adding conversational engagement meant reweighting the scoring model. Conversation depth, the specificity of questions, and how far a buyer got through qualification all became inputs. This wasn’t a small operational change. It required marketing and RevOps to rethink what “engagement” meant as a signal.
2. Define disqualification rules before qualification. LSports operates in a niche where a lot of inbound isn’t actually relevant. Sports data is a broad category. There are buyers who need a $100 API and buyers who need low-latency enterprise infrastructure for a sportsbook processing thousands of bets per minute. Those are not the same conversation. The AI needed clear rules about what constituted B2B fit and what redirected elsewhere. This protected SDR time and kept qualified conversations from getting diluted.
3. Build routing infrastructure before launching the AI. With SDR teams spread across regions and time zones, getting a lead to the right person quickly is not a handoff problem. It’s an infrastructure problem. Data enrichment and country-level redirection had to be accurate before any of the speed benefits would materialize. In LSports’ case, this was one of the highest-stakes parts of the rollout. Once it was dialed in, leads moved to the correct regional owner automatically, regardless of when the conversation started.

In practice, this meant enriching inbound conversations with company and location data, then automatically routing qualified leads to the correct regional SDR in Salesforce based on geography and account ownership.

AI Improves With Real Conversations

Because it was built on real conversations, the AI improved quickly as the team fed it more data and refined the logic. Early interactions sometimes missed context or routed conversations too cautiously, which required refining the prompts and qualification rules. The system learned from actual SDR responses, accumulated the right FAQs, and sharpened its understanding of what good and bad fit looked like in LSports’ specific market.

AI agents don’t arrive ready to represent your company. They learn from your actual sales conversations, your FAQs, your edge cases, and your buyers. The improvement curve is real, but it requires patience that most teams don’t budget for because they’re expecting a plug-and-play result.

Kivity’s advice was direct: “Trust the process. The first interactions are not the final version.”

By the second month, the impact was visible. Qualification logic sharpened. Responses became more contextual. Based on the response, the AI would ask follow-up questions about latency requirements, scale, and the buyer’s role before routing the conversation to the right SDR.

In some conversations, buyers exchanged 30 to 40 messages with the AI without realizing it wasn’t a human. In one thread, an SDR joined the conversation about 10 minutes after it began. The buyer was surprised to learn a human had stepped in at all. That was the signal the team was looking for.

Speed Changed the Entire Funnel

With Knock, LSports’ time from lead to opportunity dropped to roughly three days.

Under the old form-based motion, it often took three to four days just to book a demo. The conversation hadn’t happened yet. Qualification hadn’t started. The lead had simply moved through scheduling.

With conversational AI, qualification happened inside the interaction. By the time an SDR engaged, they already had a full enrichment packet: name, role, company, LinkedIn profile, CRM history, and the conversation transcript. Regional routing was complete. The opportunity could be created immediately.

This is the real ROI of AI-driven inbound, and it often gets overlooked. Speed isn’t just a metric. When sales arrives while buyer intent is still active, deals move faster, require less re-warming, and are far less likely to go dark between the first inquiry and the first real conversation.

Channels Shape the Experience

One thing LSports learned quickly: channel matters more than most teams expect.

Early rollout leaned heavily on Slack. That worked well in North America and Europe, where many of LSports’ buyers already use Slack daily. But engagement from APAC was noticeably lower.

Adding WhatsApp created a meaningful shift. Buyers who were less likely to start a conversation through Slack began engaging through a channel they already used every day.

The lesson is simple but often overlooked. AI-driven inbound only works if buyers can reach you through channels they actually trust and open. A frictionless experience behind the wrong channel is still friction.

Channel is also a trust signal. Buyers on WhatsApp or Slack aren’t thinking about “entering a sales process.” They’re starting a conversation in a familiar environment.

LSports noticed something interesting once these channels were active: buyers would sometimes return to the same thread days later with follow-up questions because the conversation was still sitting in the messaging app they already used every day. That kind of re-engagement is difficult to replicate with traditional email follow-up.

How Other Teams Can Apply This

If you’re running B2B inbound and considering a similar shift, here’s how the LSports team approached it and what you can implement now:

Redesign the process, not the interface. Don’t add AI on top of your existing process. Lead scoring, qualification logic, and routing rules all need to absorb conversational signals, or you’ll have a nice chatbot that generates noise your CRM doesn’t know what to do with.

Start with disqualification. It’s more important than your qualification logic. Knowing what you don’t want filters your AI’s attention toward the conversations that actually matter, and keeps SDRs from drowning in volume that looks like leads but isn’t.

Give the system time before you judge it. The first batch of interactions is not representative. The AI improves from real data, and you need enough real data before the system reflects your actual market.

Audit your channel assumptions. Where your ICP actually engages online may not be where you assumed. Check the data before committing to a single-channel rollout, and be willing to add channels that feel less familiar to your team if they’re familiar to your buyers.

Measure time to opportunity, not just lead volume. The form-fill metric will stay roughly constant because people who want forms will still use them. The signal you’re looking for is what happens to the high-intent cohort specifically, and how much faster they move once friction is removed.

The buyers who most need to reach you are often the least patient with the process you’ve built to reach them. The real opportunity is closing the gap between buyer intent and your ability to respond.