Metrics & Chill

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Metrics & Chill is a podcast about business metrics and the interesting and creative ways people improve them. Think of this show as your swipe file for discovering new and innovative ways for moving the numbers.

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109: Driving 3,500 Paid Accounts Through a Virtual Event (w/ Anna Tutckaia, ManyChat)
1w ago
109: Driving 3,500 Paid Accounts Through a Virtual Event (w/ Anna Tutckaia, ManyChat)
Why a Virtual Event?The event is called IG Summit. The website is beautiful (it actually won some awards) – But what made Anna believe this was a bet worth making? Or put differently, how could you know if a play like this would work for you?It started by analyzing their Net Revenue Retention (NRR). They found that users who signs up via educational channels or who were looking to solve problems related to Facebook or Instagram retained at a higher rate.They also stood to get the most value out of the product. So when they set a goal to drive new signups and paid accounts, they knew that using educational content around Facebook or Instagram would be successful.Besides that, they had experience with doing events in the past, though nothing to the size they were about to aim for. May 2021 they launched Instagram Automation, and were working on a go-to-market strategy to promote it. The plan was to use paid ads. But for reasons outside their control, they didn’t perform well (like the rollout for Facebook Automation had), so they needed a new plan.So Anna and the team made a quick pivot, and a big bet. The goal was to put on the biggest virtual IG summit in the world, securing 25k registrants, and 1k new paid accounts. In the end, they ended up surpassing these goals.How They Improved It1. They figured out what content resonated with their ideal customer persona (ICP) and tried to create the best content possible for that audience.They surveyed their Facebook community of existing customers, to learn what content would be the most valuable. Then they performed research to know what topics were trending, what the market was interested in learning, and what existing content was already out there.From there, they defined 3 “levels” of content the summit would include:High-level: over-arching business lessonsMid-level: more practical applicationBottom level: ManyChat experts showing how to grow business with ManyChat toolsFinally, they set the niche categories they thought would resonate best, and then found speakers who could best speak to those topics. Each speaker had the freedom to formulate their talk however they wanted but was asked to stay within the topic range they had been given.2. They asked all the speakers promote the event.They encouraged all the speakers to promote the event (though not all did), and every time a speaker joined they made a series of content they’d promote across various channels.3. They used existing, and new influencers to help promote.They had some influencers they worked with before the summit, who they partnered with to promote the product. But they also brought in new ones who they hired to specifically promote the event. Generally, they found that the existing influencers (who had already promoted the product to their audience) performed better. They also found that all the influencers got better engagement by promoting the educational event, over the product directly.4. They ran paid ads, and honed in one which drove $3 registrants 🤯Initially, they ran ads on Facebook, Instagram, and paid search. They quickly found FB ads that used the native lead form vastly outperformed the others.How well? $3 for every registrant.The results were so good, Anna had the team check for errors – thinking they might be spam emails. But after analyzing the emails against signups from other channels, along with the summit email open and readthrough rates, they found the results were truly that good. But these results didn’t come easily. They involved lots of great design and creative, and lots of tests.They also continually changed up the ads with new content every time they landed a new speaker.5. They heavily nurtured the list of registrants.They maintained constant communication with registrants the entire time leading up to the event. If they didn’t, Anna doesn’t think they would’ve seen the same results. Each registrant was sent a series of emails leading up to summit.And if they ended up registering with the product right away (as a result of seeing the marketing or ads), they were sent various In-app messages about the summit. And throughout the summit, they sent a regular volume of relevant messages to the attendees. This included messaging which emphasized, “here’s the content you’re about to consume, if you sign up for the product, you’ll be able to better take action on what you learn.”6. They tracked registrations all the way through to product signups.They had tracking in place (which users could opt out of) If that was the case, they had the registration email they could match to an account in signup. Influencers had their own campaign funnel, so they could track those referrals separately. They used an attribution model where they attributed 40% to the first touch, 40% to the last touch, and 20% to the channel they interacted with in betweenResults26k registrants and 3,500 actually paying accounts (not free trials) – 91% of whom were new to ManyChat.
109: Driving 3,500 Paid Accounts Through a Virtual Event (w/ Anna Tutckaia, ManyChat)
1w ago
109: Driving 3,500 Paid Accounts Through a Virtual Event (w/ Anna Tutckaia, ManyChat)
Why a Virtual Event?The event is called IG Summit. The website is beautiful (it actually won some awards) – But what made Anna believe this was a bet worth making? Or put differently, how could you know if a play like this would work for you?It started by analyzing their Net Revenue Retention (NRR). They found that users who signs up via educational channels or who were looking to solve problems related to Facebook or Instagram retained at a higher rate.They also stood to get the most value out of the product. So when they set a goal to drive new signups and paid accounts, they knew that using educational content around Facebook or Instagram would be successful.Besides that, they had experience with doing events in the past, though nothing to the size they were about to aim for. May 2021 they launched Instagram Automation, and were working on a go-to-market strategy to promote it. The plan was to use paid ads. But for reasons outside their control, they didn’t perform well (like the rollout for Facebook Automation had), so they needed a new plan.So Anna and the team made a quick pivot, and a big bet. The goal was to put on the biggest virtual IG summit in the world, securing 25k registrants, and 1k new paid accounts. In the end, they ended up surpassing these goals.How They Improved It1. They figured out what content resonated with their ideal customer persona (ICP) and tried to create the best content possible for that audience.They surveyed their Facebook community of existing customers, to learn what content would be the most valuable. Then they performed research to know what topics were trending, what the market was interested in learning, and what existing content was already out there.From there, they defined 3 “levels” of content the summit would include:High-level: over-arching business lessonsMid-level: more practical applicationBottom level: ManyChat experts showing how to grow business with ManyChat toolsFinally, they set the niche categories they thought would resonate best, and then found speakers who could best speak to those topics. Each speaker had the freedom to formulate their talk however they wanted but was asked to stay within the topic range they had been given.2. They asked all the speakers promote the event.They encouraged all the speakers to promote the event (though not all did), and every time a speaker joined they made a series of content they’d promote across various channels.3. They used existing, and new influencers to help promote.They had some influencers they worked with before the summit, who they partnered with to promote the product. But they also brought in new ones who they hired to specifically promote the event. Generally, they found that the existing influencers (who had already promoted the product to their audience) performed better. They also found that all the influencers got better engagement by promoting the educational event, over the product directly.4. They ran paid ads, and honed in one which drove $3 registrants 🤯Initially, they ran ads on Facebook, Instagram, and paid search. They quickly found FB ads that used the native lead form vastly outperformed the others.How well? $3 for every registrant.The results were so good, Anna had the team check for errors – thinking they might be spam emails. But after analyzing the emails against signups from other channels, along with the summit email open and readthrough rates, they found the results were truly that good. But these results didn’t come easily. They involved lots of great design and creative, and lots of tests.They also continually changed up the ads with new content every time they landed a new speaker.5. They heavily nurtured the list of registrants.They maintained constant communication with registrants the entire time leading up to the event. If they didn’t, Anna doesn’t think they would’ve seen the same results. Each registrant was sent a series of emails leading up to summit.And if they ended up registering with the product right away (as a result of seeing the marketing or ads), they were sent various In-app messages about the summit. And throughout the summit, they sent a regular volume of relevant messages to the attendees. This included messaging which emphasized, “here’s the content you’re about to consume, if you sign up for the product, you’ll be able to better take action on what you learn.”6. They tracked registrations all the way through to product signups.They had tracking in place (which users could opt out of) If that was the case, they had the registration email they could match to an account in signup. Influencers had their own campaign funnel, so they could track those referrals separately. They used an attribution model where they attributed 40% to the first touch, 40% to the last touch, and 20% to the channel they interacted with in betweenResults26k registrants and 3,500 actually paying accounts (not free trials) – 91% of whom were new to ManyChat.
108: Improving Scaled to Productivity (w/ Amanda Ono, Resolver)
Sep 14 2022
108: Improving Scaled to Productivity (w/ Amanda Ono, Resolver)
Why Scaled to Productivity?The metric she focused on is Scaled to Productivity: how fast they could get new hires to 70% utilization while feeling confident, and able to lead a successful implementation with the biggest customers.As Resolver’s product matured and they started stabilizing gross margin, they started to think about scale.Specifically, the best ways to maintain their margin while adding headcount.As a SaaS company, they were growing at 25-30% YOY in terms of revenue. They had a couple of levers to pull to achieve this: Utilization: ensuring individuals have utilization targets that they’re hitting consistently. But their philosophy wasn’t to have utilization targets in the high 80s or 90s, because they don’t want to burn people out. Plus, they want people to still have time to learn, grow, and understand what the platform does. Hire more people. But eventually, that would hurt gross margin (especially at a fast-growing, global organization).So Amanda asked, “what if we could get more team members to be effective with our customers, faster?”. In other words, what if they could get employees trained and effective in 5 months, instead of the 8-9 months it typically took?They had a strong belief that this would empower employees and increase profit. And when they looked at their services forecast model, they saw that if they improved the rate at which people hit their utilization targets, it would have an enormous impact on revenue.So they worked to improve it, in 5 main steps.How They Improved It1. They got buy-in from leadership, and hired someone to own it.Companies often make a project like this 10% of someone’s job, leading to poor results.They knew they’d need someone fully focused on it. So they got buy-in on the 5-month goal and hired someone to own it.2. They created an initial training plan, by reverse-engineering their goal result.They asked, “what would need to be true, in order to get employees to 70% utilization in 5 months?” The answer to that question helped from the initial training framework.They found there were 3 “prongs” they could focus training on:Product: knowing the product, and being able to configure it to client needs.Project: knowing how to implement a SaaS project using Revolver.Domain: understanding the domain of risk or corporate security.They already try to hire team members with domain expertise. And many come with experience implementing projects at a SaaS company. So they focused the bulk of the training on the Product side.3. They performed a “needs analysis” to learn what content was missing from the past program.After they formed their initial framework, they also talked to all the new employees and asked them what they would’ve liked to be successful in their first, or sixth month. This provided an active feedback loop and helped fill any gaps their initial plan had left out.To do this, they formed cohorts of employees to survey who had been hired within 30-60 days of each other. Then they batched them by role.They analyzed cohorts on a couple of factors:How proficient were they when they initially joined? (e.g. were they an early, mid, or seasoned contributor when they came into the training program)How quickly did they ramp up?And how quickly did they achieve success?Early employees could offer what education would’ve helped them be more successful. And the Resolver team would be able to further enhance the new training program to fill these gaps.4. They implemented a mentorship program, by incorporating seasoned employees.They took employees who had been part of the team for 12+ months and had them serve as mentors or learning coaches for new hires. These mentors would host Q&As with new team members and help them apply their new knowledge to real customer needs & situations. They also provided crucial feedback to help improve the training program based on their experience implementing successful projects with customers.5. They added a feedback feature to the training material itself.After all the feedback they received, they built the content for the training program. In it, they incorporated a feedback system so trainees could leave feedback in real-time as they were going through it.ResultsAfter the new training program was done, they ran 2 cohorts through it, and analyzed how much revenue was generated by:An employee who scaled to productivity using the old training (in 9 months), vs one who completed the new training (in 5 months).The results?A 25% improvement in revenue, in the 5-month cohort. When they applied this to all the new hires they made, they found this improvement in Scaled to Productivity drove an additional $700,000 in revenue.
107: Driving Inbound Sales Accepted Opportunities (SAO's) in 3 Steps (w/ MJ Peters, CoLab)
Sep 7 2022
107: Driving Inbound Sales Accepted Opportunities (SAO's) in 3 Steps (w/ MJ Peters, CoLab)
Driving Inbound SAOsWe got to chat with the brilliant MJ Peters (VP of Marketing at CoLab), to hear about the 3 main levers she pulls to drive inbound SAOs. Namely:EyeballsMessagingFirst Sales CallWe’ll go through a summary of each of these levers below, and pull out some insights on how she’s using them to grow CoLab’s SAOs and revenue.How They Improved ItLever 1: EyeballsMJ works to get as many of the right eyes as possible to look at the brand and messaging. This means creating content for 2 categories:Demand capture (e.g. SEO & paid search)Demand creation (e.g. paid ads on social)For demand capture content, she makes sure Product Marketing and Demand Gen work in sync, so the messaging is consistent. The ad should offer a hook or summary, but the site should expound upon it.When she’s running social ads, she’s looking at engagement & CTR as a leading metric of how it’s performing. As it runs, she’ll look at profiles of who comments or likes, and adjust the audience over time to make sure it’s reaching only the most relevant job titles. For demand capture content (typically paid search or SEO), there’s less flexibility over the messaging, because the prospect is looking for a specific thing.So her goal is to respond from a positioning perspective to meet prospects where they’re already at.Lever 2: Messaging on the websiteOnce she gets eyeballs on the website, she makes sure what they’re reading resonates with them and leads them to convert. At this point, she’s used content on outside platforms to catch prospects with a hook and generate demand to learn more. And now that those prospects are on the website, she has a better opportunity to elaborate on the key value points she shared off-platform.To help her craft the best messaging, MJ has 1:1 calls with customers and listens to sales recordings on Gong. First, she identifies the use case they came to CoLab for. Then she sifts through dozens of pains/talking points and distills the top 3 or 4 that come up the most. These will become the 3-4 talking points on that specific use case page.For example, one use case may be using CoLab to lower costs, by designing costs out of their products. So MJ will identify the top 3-4 pain talking points around that, and use them on that use case page.Ultimately, this allows her to have the best chance at saying things that resonate with customers and drive the highest conversion. And as we mentioned earlier, she carefully maps this messaging in the “get eyeballs” stage, so demand gen is more effective and the prospect experiences more consistency.Lever 3: The first sales callOn the first call, MJ makes sure what the prospect hears, lines up with the marketing messaging they saw.In other words:Find the promised value that drove the prospect. Then give them a taste of that value, right away, in the first call.To help her do this, MJ uses different demo booking forms on each use case page. So when a prospect books a demo, she can dig into the CRM to let the rep know what use case the prospect is interested in, and what pages they visited.Consider the traditional experience:The prospect reads a use case page about how your product will help them reduce time and save money. They come excited to learn how you’ll help them do that. But on the first call, they get peppered with 25 discovery questions.This is a poor, unhelpful experience.Instead, marketing can dig into the deal in HubSpot and see that the Contact booked a demo on your Solutions page around “saving time”. They can relay that context to the rep, so the rep highlights exactly how the product saves time.By being involved in the first call, MJ’s team is better aligned with sales and delivers a more relevant experience for the customer. She feels many companies invest heavily in the first 2 levers, but ignore this one, which results in a leaking funnel at this stage.ResultsMJ only recently started the role, and has spent most of the time heavily investing in refining their messaging on all these levers. But it’s already starting to pay off.In all her time in marketing, she’s never seen messaging have as big of an impact as it has at CoLab. She’s also seen the quality of SQLs and SAOs in the pipeline become much higher, specifically in terms of firmographic fit and qualitative motivation for reaching out.
106: Growing Organic Traffic to the Blog (w/ Fara Rosenzweig, WorkRamp)
Aug 31 2022
106: Growing Organic Traffic to the Blog (w/ Fara Rosenzweig, WorkRamp)
Reaching New Prospective CustomersSince most of WorkRamp’s ideal customers might not be ready to make a purchase decision, or even know much about the category, they set out to bring in more new potential customers to the blog. The goal was simple: deliver helpful content visitors would bookmark, share, and come back to, in order to build brand awareness and trust with WorkRamp.WorkRamp can educate these prospective customers on immediate questions or needs they have, and build familiarity with their brand and what they do. And eventually, when they’re ready, they’ll come back to signup or purchase.How They Improved It1. She focused on top-of-funnel content to reach a wider base of new prospective customers.WorkRamp wanted to bring in more *new* people to the website, and introduce them to the brand.Since most visitors wouldn’t be ready to make a purchase decision, she decided to focus heavily on top-of-funnel content to build trust & familiarity with Workramp so visitors would be more likely to come back and try the product when they’re ready.2. They performed an audit to see what topics were playing, and which weren’t.When Fara got started, there wasn’t a lot of content strategy in place. The team evaluated current performance to know what was working & what wasn’t.If an existing topic was resonating and gaining traffic, they set out to repurpose or elaborate on it. If a topic wasn’t getting much attention, they’d stop allocating resources to it. This helped them know where to invest their time and budget in the early days.3. She listened to sales calls every week, to learn what topics customers would be interested in.Fara built a habit of listening to customer calls every week to learn common customer questions. She’d create content based on these common questions, problems, or educational needs customers had. She’d pair this research with KW research, and create content that had significant search volume – and mostly importantly – resonated with their target customer.4. She set a practical “quality rule” for each piece of content.Fara wanted to create content that readers would bookmark, share, and revisit. To do that, she created a simple rule. Every piece of content needed 1 valuable thing readers could leave with.In other words, she tried to ensure that every piece of content had really valuable insight readers could leave with and put into practice. Even if they outlined “5 ways to ______”, she’d focus on the 1 thing readers could leave with – if they took nothing else away.5. She analyzed what competitors were doing, to find how they could take a different angle on their content.Even though competitors would cover the same topics, Fara wanted to make sure WorkRamp had a unique angle or take on saying the same things, to stand out from the crowd.6. They tracked the impact of their content further down the funnel.Besides organic traffic, Fara’s team keeps a close eye on contacts created via LI (from the brand account), social media engagement & traffic to the site, and ultimately, demo requests & MQL attributions.ResultsAs a result of all this, Fara and her team were able to increase Organic Traffic to the Blog from
105: Growing Lead to Opportunity Conversion Rate by 49%
Aug 24 2022
105: Growing Lead to Opportunity Conversion Rate by 49%
Driving Demand for ClientsJonathan and the team at Omni Lab are focused on using paid channels to generate demand that drives pipeline for clients.The primary, lagging indicators they track are:Demos for sales led or Trials for PLGPipelineLead to OppOpp to RevCAC PaybackRevenueAlong with a host of other leading metrics, to know how the ads are performing. By focusing on Lead to Opportunity, they’re able to gauge how effectively they’re targeting the right audience, with the right messaging, who eventually reach out to book a call with sales and become opportunities.How They Improved It1. They helped refine targeting by analyzing where the Client had been successful in the past.They looked at case studies, social proof, quotes, and best-performing deals in the CRM.One insight this revealed was that most of the “best customers” came from employee sizes of 10-50. But the client had been targeting companies much bigger than that.This process essentially allowed them to reverse engineer who the best clients were (who gave testimonials, case studies, etc) and refine the targeting to reach more of the same.A huge benefit of starting with a niche audience in paid, is that they were able to focus their budget in one place, vs just spreading it across a wide swathe of geo, industry, company size, etc.It also allowed them to add better personalization, which drove higher conversion.For example, they could make the creative more specific: logos of companies that look like them, or case studies of peers they’d know.2. They improved the booking flow.They’ve tested every possible booking flow with clients, but have found the most success starting with a form, then going to a booking tool like Calendly or Chili Piper.When choosing a time, prospects have to go off-site to open their calendar & see what times work for them. That means there’s always a % that don’t come back. By using a simple form as a first step, you can send the booking form and remind them, to try and get them back.3. They improved messaging by studying what worked best in the past.Like many early-stage companies, this client didn’t have a dedicated product marketing team. So they got an overview of the ICP’s articulated pains, values they wanted, and overall buyer journey.How?Reviewing early outbound emailsTalking with the founderListening to sales callsTalking to sales repsThis allowed them to create messaging that had the best chance of resonating, without the benefit of in-depth research. Jonathan believes that if you’re really early, this messaging may just be coming from the Founder’s brain. The key is: don’t wait for it to be perfect. Get it good enough, based on some positive input, and start testing.4. They performed “micro-tests” on that messaging.Before putting thousands of dollars of spend behind it, they did small tests with the new target audience to see how the messaging resonated well. Jonathan also said that this is where most people go wrong when testing messaging or creative: they test too many things.They change creative and visuals, messaging, and CTA, so it’s impossible to identify what change made the biggest impact or how each piece is performing.5. They optimized for the audience consuming the messaging in-channel.Rather than try and optimize for immediate conversions or website clicks, they focused on getting more consumption of the message on-platform.6. They resolved any uncertainty buyers felt in the retargeting layer.They used retargeting ads to answer common objections and questions prospects had, and to provide social proof so they felt more comfortable with the client.This meant that by the time the retargeted prospects did become leads, they converted at a much higher rate because they were already more familiar with the company and had many of fears/uncertainties answered.ResultsThese steps led to a 49% increase in the Client’s Lead to Opportunity Conversion Rate (from 25% to 74%).
104: Growing Inbound Leads by 50% (w/ Brad Hoos, The Outloud Group)
Aug 17 2022
104: Growing Inbound Leads by 50% (w/ Brad Hoos, The Outloud Group)
Why Inbound Leads?Like many agencies, they relied for years on doing great work, delivering results, and getting referrals. They had a growing brand and a strong reputation and were growing year over year.But recently, they finally decided to invest more in marketing, for 2 reasons.First, they were structurally ready for it. They had a strong team and processes, able to handle an influx of growth. Second, they were ready to hire a dedicated person to own growth. So they brought in David Hoos (a proven B2B marketing leader) to lead marketing & growth efforts.They decided that high-quality, inbound leads coming in through the website would be the best reflection that their marketing efforts were working. So that served as their primary KPI for success.Then they took a few strategic steps to grow that number.How they moved the needle1. They took inventory of current performance.They analyzed past data to learn what had stagnated, what was trending in the wrong direction, and what was trending in the right direction. This included studying lead quantity and quality, organic traffic, and kw rankings.2. They focused on building domain authority by sharing original thought leadership.They hadn’t invested in SEO up to that point and were getting outranked by agencies with less expertise, performing worse quality work.So they set out to improve their domain authority.They had published a number of pieces of content, sharing original research, insights, and thought leadership. Some of this lived on their blog, but much was gated behind an email wall, or in white paper form. Most of the content was created to showcase their experience with clients during the sales process.Making the decision to “ungate” it, they realized they had to unapologetically see themselves as thought leaders in the space, and be proud to share what they knew with everyone. Sharing these insights has help gain them additional attention, backlinks, and publicity.They’ve shared the insights at conferences, through PR, podcasts, and more. As a result, they’ve used it to build their domain authority.3. They started speaking at events.They found that traffic would increase leading up to the event, spike the day of the event, but then go back to normal.But it was a great opportunity to make an impact, and continue building domain authority and brand awareness.4. They guested on podcasts.They’d find podcasts where listeners were their target audience, and aim to deliver as much value in the interview as possible. This drove site visits and backlinks, further advancing their SEO efforts.5. They put their people front and center.They started showcasing the actual experts and thought leaders: their team. As a services business, this helped prospective customers trust them, and feel like they knew who they’d be working with.Combined, these efforts produced a bigger cumulative effect:Someone might search for “influencer marketing agency”They’d find The Outloud Group in a list of top agenciesSo they ask peers if they’ve worked with themThen hear them on a podcast or at an eventThe resultsThey increased high-intent inbound leads, sourced through their website, by 50%.
103: Gaining 1,200 New MQLs via Virtual Events (w/ Ollie Whitfield, VanillaSoft)
Aug 10 2022
103: Gaining 1,200 New MQLs via Virtual Events (w/ Ollie Whitfield, VanillaSoft)
Why MQLs?If you spend any amount of time on LinkedIn, you might see any number of posts proclaiming that “the MQL is dead”. But Ollie and his marketing team at VanillaSoft don’t think so.In fact, MQLs are the primary metric Ollie works to move the needle on. They share a common metric with the sales team to ensure that they’re driving high value MQLs who have a higher likelihood of converting.To do that, they employ a number of channels, ranging from paid ads, to SEO, trade shows, and webinars. Until recently, they had never tried virtual events.How They Improved ItThe prior quarter, Ollie’s team had a big, scary MQL goal. They hit it, but only barely.Then, in the next quarter, the goal was raised significantly. Ollie knew they’d have to change their approach in order to hit it.So he decided to invest heavily into virtual events.In the prior quarter, Ollie’s team hosted an all-day virtual event. It was imperfect and exhausting, but they learned from it. He was determined to host another one (new and improved), in order to secure the new MQLs he needed.Here’s how he did it…He got great speakers, who could also help promote the event.He chose speakers who were incredibly smart and well-spoken. But more than that, they had to be able to help promote the event to a relevant audience, so the content would actually get seen.He made the event 1-month long.The first conference they ran was an 8-hour day, jam-packed with back-to-back sessions. That format was rough on both the team and attendees, so this time, they tried a new approach.They’d aim for 2 sessions a day, 30 minutes each session, for 1 month straight. That worked out to 45 total speakers, presenting 45 sessions, across 22 days.This new format took longer to plan, but provided 4 main benefits:Benefit 1: It was more relaxed.Attendees could consume events they were interested in all month, without giving up an entire day of work.Benefit 2: It provided ongoing content to market.Ollie found that with their single-day event: they promoted it, and it was done. By changing the format they were able to continually promote new material and build on the success of past sessions.Benefit 3: It provided social proof to help them secure additional speakers and sponsors.The day the conference launched with its initial lineup, Ollie was able to keep doing outreach and gain an additional 14 speakers and sponsors. Prospective speakers or sponsors were able to see what they’d be participating in. They could also opt-in late in the game, without feeling like they’d missed the opportunity.Benefit 4: It drove more attendance.With 45 speakers, if each speaker brought just a handful of their audience, Ollie knew they’d have great attendance.Ollie promoted 1 new speaker, every few days.He felt he couldn’t do justice to all 45 speakers if he tried to promote them all in 1 big announcement.So instead, he’d focus on promoting a new speaker every few days. This allowed him to properly highlight the skills, expertise, and session that each speaker was bringing to the table.They created generous, strategic sponsorships.Some of the sponsors came from ABM accounts. This gave them the ability to continue building those relationships, while offering them something of value. And some were friends of Ollie’s, who came from smaller companies.They didn’t charge these sponsors. Ollie wanted to be able to have the relationships be truly win-win. VanillaSoft would get the benefit of more promotion and attendees. And the Sponsors could gain leads and exposure without risking a huge budget.They used HeySummit to host an event website.This provided each speaker with their own landing & registration page, one place to house live and on-demand content, and a sponsors page.ResultsThe pace was exhausting but drove massive results:Ollie and his team exceeded their high quarterly goal, bringing in 1,200 new MQLs from the event.
102: Generating SQLs via LinkedIn Ads (w/ Gabriel Ehrlich, Remotion)
Aug 3 2022
102: Generating SQLs via LinkedIn Ads (w/ Gabriel Ehrlich, Remotion)
Insights on Driving SQLs via LinkedIn Ads:1. Use benchmarks to identify competitive advantages.Look for instances where SQL rate (lead to meeting ratio) is 2-3x higher than average, and come up with a hypothesis as to what caused that growth.Then, see if you can duplicate it in another campaign.Once Remotion finds meaningful variance, they determine if the higher performance was owing to factors that can be duplicated.If so, they’ll increase the budget and spin off a new campaign where they lean into the things that made the former campaign perform so well.2. Get qualitative insights into ad performance.His team uses common sense, and deep familiarity with their clients to create a hypothesis of why a campaign saw meaningful change in performance.By talking with clients, they’re able to learn what’s happening that might be affecting performance.For example, after talking with the client they learn that John – the company’s best SDR – is on vacation.This is the cause of lower results down-funnel.And since they have access to their client’s CRMs accounts, they’re able to be proactive in looking at any other factors that impact ad results that they might not have seen by staring at performance numbers in the Ad platform.3. Remain “strategy agnostic” until you find what works for you.Gabriel has seen a lot of commonly accepted truisms fall on their face when applied to Clients in different countries or industries.4. Look at performance often enough to derive insights, but avoid knee-jerk decisions.Remotion gives each client gets their own real-time dashboard which shows:CPLLast 7-day CPLTrend over last 30 daysComparison to previous 30 days… and more.They know what a client’s current CPL is every day.But for metrics further down the funnel, they evaluate them monthly. This helps them make more informed decisions based on proven trends, and avoid knee-jerk reactions to a bad (or good) week.5. Determine your campaign goals early.Most companies run 2 types of campaigns:Direct response = promote your product, get someone to talk to youContent = promote your POV & provide valueEach generates different outcomes, so choose the one that best serves your goals. If you aren’t sure which type of campaign you want to run, Gabriel advises running both, then determining the CPL. Benchmark your performance to know if one is higher than the industry average. If it is, use that one.6. What companies get wrong about LinkedIn ads:Under-investingBeing inconsistentBeing unclear about their goalNot having messaging honed inHaving an inactive audience on LinkedInNot being ready (too early, no product-market fit)7. Testing messaging through LinkedIn ads can be costly.You need a lot of data to see how it impacts SQO rate.For example, you want to run 2 tests: so you need 50 leads on each (100 total, to have enough meaningful data) > and your CPL is $100.That means 1 test costs 10k. This can be great if you have a 100k budget. But if your budget is 15k/mo, then it means you spent almost an entire month testing 1 message variant.If that’s worth it, that’s great. But Remotion finds that often, it’s not significant enough to justify the investment.
101: Driving 70% of Qualified Pipeline via Inbound (w/ Pete Lorenco, Alyce)
Jul 27 2022
101: Driving 70% of Qualified Pipeline via Inbound (w/ Pete Lorenco, Alyce)
Why Qualified Pipeline via Inbound?The whole team is focused on driving net new logo revenue. So Pete focuses his team on qualified pipeline to contribute to that goal, and be aligned with the rest of the team.They define “pipeline” as “total booked revenue” (= when a scheduled demo meeting takes place). Since they aim for a win rate of ≥ 20%, this allows Pete to work backward from their revenue goals, and determine how much pipeline he needs to drive to help meet it.How They Improved It:They focused on understanding their audience better.They get on sales and customer calls weekly. This gives them insights around pain points and needs prospective customers have.These insights help them continually optimize their messaging, in order to be more helpful and relevant. It also helps them learn where their target customers spend time or pay attention.This means that when they make big bets on channels to invest in, they aren’t guessing.They invested heavily into refining their messaging & positioning.In a world where features are easily copied, Pete invested in differentiating Alyce by crafting a unique point of view and go-to-market message. This positioning provides a source for the entire team to draw from when they need to craft messaging or marketing creative.They brought in Dave Gerhardt, who helped them further refine how they thought about positioning and messaging for Alyce in a new and unique way.And once they had some concepts, they tested the new messaging on their homepage using Wynter, in order to look for leading indicators that the messaging would be successful and land the right way.They focused on harvesting more existing demand.They leverage about 25% of their resources and team on capturing existing demand. This includes using intent data to trigger more targeted outreach, retargeting on social, and a mix of branded & non-branded PPC programs.They focused on creating new demand.The biggest bet they’ve made is finding ways to create new customers and generate demand. They’ve done that in 2 broad steps:1. Create relevant and insightful content2. Distribute that content everywhere their target audience isThey made big bets on:Events (micro & virtual)Social (paid & organic)Co-marketing with other brandsInvesting in evangelists who speak on podcastsAnd communitiesBecause they’re tracking self-submitted, qualitative attribution, they’re able to see the efficacy of these channels and find the ones that are most effective.So far, it’s paying dividends. Top attributed channels are LinkedIn, Google Search, and Communities/Events.They approached communities with 2 main focuses:Bring value & education (don’t just talk about Alyce)Find ways to let members experience Alyce’s giftingFor example, members might be sent gifts upon joining or completing certain milestones. This allows these marketers (= the community members they’re reaching) to experience the value of Alyce in a more natural and generous way.ResultsAlyce had great momentum from past marketing leaders. With that as the foundation, this framework helped them increase the % of inbound qualified pipeline to 70%.Full episode here.
100: Doubling Free-to-Paid Conversion Rate (w/ Amanda Natividad, SparkToro)
Jul 20 2022
100: Doubling Free-to-Paid Conversion Rate (w/ Amanda Natividad, SparkToro)
Why Free-to-Paid Conversion?Amanda had a gut sense that since “audience research” was still pretty early and search volume was relatively low, they needed to nail the onboarding experience when people did give them a try.She started working with Forget The Funnel, who helped them identify 2 big opportunities:1) Increase free-to-paid conversion.2) Improve the onboarding experience.So they focused on growing their free-to-paid conversion %, and got to work improving onboarding.How They Improved ItImproving the onboarding flow.At the time, SparkToro's onboarding flow had 15 (or so) steps and a 10% completion rate, which was above average. Despite that, they were still addressing churn and getting questions about the product, so Amanda knew there was room for improvement.So she worked with Ramli John, who helped them improve the sequence. They did this by reducing it to 8 steps, and having Rand Fishkin (founder) trim his welcome video from 5 minutes to 2.Next, they updated the onboarding messaging, making it more concise and using a more active voice.Finally, they made sure every onboarding step mapped to 1 single feature. Previously, they had introduced new users to "list creation" and "outreach" in the same onboarding step. Amanda noticed that not as many people were creating lists, so they broke these into 2 steps.These changes alone took their onboarding completion rate from 10% to 15%. And even though Amanda couldn't prove users were actually consuming the messaging more than before, she knew it was easier to understand, quicker to get through, and it drove users to complete 1 successful search so they could reach the “aha” moment faster.Creating a behavior-based email sequence.In the early days, Rand would send personalized welcome emails himself. Later, this became 1 email welcoming users to the product, with subsequent emails being sent to remind users of upcoming monthly charges.Amanda knew there was lots of room for improvement here, but she faced one major challenge: SparkToro had a very wide use case.It's used by a lot of different companies, for a lot of different things. This meant that doing "1 size fits all" onboarding emails wasn't going to cut it.So she created a "behavior-based" email sequence, with 3 main goals:1. Get people to "value realization" as quickly as possible2. Help users get into the habit of using SparkToro more often3. Get users to use more features, and realize it's powerShe worked with Casey Henry, SparkToro's co-founder, to build out workflows that would group users into logic-based cohorts. Depending on the cohort/segment they were in, they'd experience a slightly different onboarding email sequence.For example, the first action someone takes is signing up for a free account. Ideally, the 2nd action they’d take is running a search. So if someone performed a search, they'd get a welcome email that would suggest other searches they might try. But if they signed up and didn't make a search, they'd get an email suggesting first searches to try, that might be beneficial to them (based on inputs from the customer).This allowed them to provide specific help, based on prospective customers' needs and use cases.Launching "Office Hours"Amanda started a series of live sessions where anyone could ask questions and get answers in real-time on a consistent day/time every week.They'd promote this to new users in onboarding emails, but it was open to anyone. They regularly get 1,000 people watching, with as many as 1,300 on some sessions.This provided a way for curious, would-be customers to learn more about the product in a no-pressure environment. And existing customers can get answers to specific questions they faced while trying to adopt the product for their own use.ResultsIn 4-6 months, the team doubled their free-to-paid conversion, adding more revenue without any new inbound channels.
99: Growing HIRO Pipeline by 76% (w/ Chris Walker, Refine Labs)
Jul 13 2022
99: Growing HIRO Pipeline by 76% (w/ Chris Walker, Refine Labs)
Why HIRO Pipeline?Refine Labs helps drive demand and pipeline revenue for SaaS companies from Series A through D. When they hit 30~ Clients, the team went to measure how many pipeline dollars those clients would get for every $1 they spent in ads. Chris wanted to be able to show what the growth of their pipeline was (across all clients) from the time they started working with his team, to then.But he had a problem. He realized that out of all their clients, none defined pipeline the same. Every single one had different definitions. For exome companies, “pipeline” meant that the lead booked a meeting with an SDR, and was in a stage where the deals convert at So Chris created a new pipeline revenue metric that could be easily adapted by all clients (and non-clients who wanted to), and would allow them to benchmark their performance against others.They define HIRO Pipeline as leads that come in through a high intent source (book a call, schedule a demo, etc) with win rates greater than 3% from lead-to-win, and reach a deal stage in your pipeline that converts at a 25% rate for that cohort of opportunities.These two qualifiers mean that if the deal stage starts to close below 25%, marketing needs to change the stage that HIRO is defined by (to a 25% or higher one) so they’re always aligned to sales performance.It also helps align marketing to revenue, without having to wait for the lagging metric of actual revenue to come in – because it’s based on a secure win rate.How They Improved ItUsing qualitative attributionFirst, Chris believes it’s important to understand that HIRO Pipeline’s efficacy isn’t going to be clearly shown by traditional attribution software. It requires a blend of qualitative and quantitative attribution. For most, this can be done by adding a simple open text field in the onboarding process, asking prospective clients how they heard about you.Balancing focus and budget between creating demand, and capturing demandChris believes the main key to driving HIRO Pipeline is striking the right balance between creating demand and capturing demand.Capturing demand is waiting in channels where people have demonstrated intent, are “solution-aware”, and are actively looking to buy something. For example, Google Ads or product review sites like G2.Creating demand is spending time reinforcing your messaging in channels where people are not in the market for your product or service. They may not be “solution-aware”, and don’t have intent to buy what you’re selling.Chris believes the key is to have two different strategies to reach each of those audiences.Chris believes that because companies rely so heavily on attribution software, they’re only focused on the “channels that work”, which are all demand-capturing channels.This means there are only so many buyers these companies can reach, and worse still, they have no control over how that demand was generated. Instead, companies must focus more on creating demand (vs capturing it), so they have control of the flow of new buyers entering the market.This means most companies must change the way they think about and approach demand generation. For example, if you don’t draw a distinction between “demand capture” and “demand gen” channels, you’ll end up treating the audience in each of those buckets the same. Where in reality, one audience is ready to buy and wants to consume one type of content, while the audience in the other is not going to buy and is interested in an entirely different set of content.For Refine Labs, this means using “demand gen” channels to help clients amplify messaging that educates clients about:the categorythe business problems that the Client solvesHow that Client has driven success for other customersDifferentiating features the Client has, that competitors don’tetc.Chris believes marketing teams need to take those elements, say them in compelling ways, and serve that messaging up natively in demand-gen channels that prospective buyers are already in. The goal is not to convert the prospective customer in that moment, but rather to educate them and keep your company top of mind.This means that instead of driving a person on LinkedIn to download an e-book, you might run an impression-based video ad that showcases the growth you drove for a client, or a written post breaking down what people should know about the category you’re in.The idea is that you plant the seed in this person (who has consumed this messaging) in the belief that they will end up sharing your company in a Slack channel, with peers at an event, or through a LinkedIn DM. And then someone from their network or company will come directly to your site when they’re ready to buy.ResultsRefine Labs has been applying that framework for customers since Day 1.They researched a cohort of 20 customers from B2B SaaS companies that had clean, historical data for 6+ months before starting to work with them. They then compared the 6 months prior to working with Refine Labs to the 6 months after working with Refine Labs, specifically drilling down to the HIRO metric.Across those 20 clients, the median increase in pipeline was an impressive 76%. This means a series C or D company doing $2m in pipeline before Refine Labs was doing $3.5m~ after working with Chris’s team.View the full episode here.
98: Increasing Sales Efficiency Ratio (w/ Josh Ho, Referral Rock)
Jul 6 2022
98: Increasing Sales Efficiency Ratio (w/ Josh Ho, Referral Rock)
The metric: Sales Efficiency RatioIn this episode, we’re covering Sales Efficiency Ratio: which the Referral Rock team defines as “the ratio of salesperson sales, vs non-salesperson generated sales.”John Bonini chats with Josh Ho, founder and CEO of Referral Rock, to learn how they improved their Sales Efficiency Ratio, and as a result:Onboarded customers fasterIncreased user’s “speed to launch” rateRemoved a bottleneck to growthAnd were able to do more, with lessWhy Sales Efficiency Ratio?There were two main reasons why Josh and the team decided to try and move the needle on this metric:Selling primarily through sales reps was successful at first, but eventually became a bottleneck for growthThey wanted to lean into product-led growth and grow the self-service side of their productBefore improving this metric, 90%~ of sales were closed by the sales team. This worked well for a while, but eventually became a bottleneck to growth.The problem was, as the leads increased, so did the need for trained sales reps. And for a bootstrapped company like Referral Rock, this was costly in time & money.It also made it challenging to test new channels because they didn’t have the ability to scale the sales team as fast as leads would come in. For example, if they decided to heavily invest in paid ad channels and it ended up driving lots of leads, they’d have to scramble to hire enough sales staff to help support the growth.Besides all that, they had been intrigued by PLG (product-led growth), and how much more efficient that model could be for a SaaS company like theirs.Up until that time, they were using traditional sales-led growth. The primary CTA drove users to book a demo, and 90% of their closed deals came from this sales-led method.There was a self-service option, where users could start a free trial and build their program without input or assistance from sales. But only 10% of closed deals came through that route.So they set out to improve their sales efficiency, by increasing the number of deals that were closed via non-sales methods.How They Improved ItThey made product improvements to foster more self-service.They began working on shipping more PLG-inspired features to improve their existing self-service onboarding and upgrade flow. This way, if users preferred to set up their own referral program or upgrade their account, the experience was smoother for them.They had CSMs lead group demos, then pass that group off to the product itself.Before, they’d try to get important internal stakeholders onto the call, and take a more heavy-handed sales approach via sales reps.With this “lighter touch” approach, they’d take a group of interested users, show them a demo and answer their questions, and then hand them off to the product ( = the self-service / PLG route they developed).They initially built this “group demo to product” team by stealing from their CS team.They started with one team member in particular who knew the product inside and out, and who had been on some sales calls before. He was critical in helping frame out the role, and make this new model more efficient.Once they had the process in place and a better idea of what the role looked like, they began hiring outside talent to expand the team.They promoted their two CTAs (“Book Demo” and “Start Free Trial”) equally.They updated the layout and design of their site to give equal primacy to the two main CTAs. This let users choose how they wanted to buy.They introduced intelligent routing which sent users to self-service or sales, depending on various criteria.First, they implemented various tools & workflows in the product to get a better idea of what stage the potential buyer was in, and what type of company they were.Then, based on those inputs, they’d put them in pre-set groups or buckets.From there, they could route them to either the lighter-touch sales method they had developed (which resulted in self-service), or the traditional sales method, depending on which would serve them better.In addition to that, they implemented a lead score mechanism to route the right leads to the right person.Finally, they retooled their workflows to better serve prospective customers depending on which bucket they fell into.For example, users in the CSM-led, "lighter-touch” sales group might get 1 series of emails and messaging. While users in the traditional sales bucket might get an entirely different set of messaging.ResultsIn 6~ months these efforts resulted in them changing their Sales Efficiency Ratio ratio from 90/10 to 50/50.In practical terms, this meant that:Customers were onboarding fasterThe team could expect the “speed to launch” rate (how fast customers get their referral programs launched) to increase significantlyHiring and training new sales reps was no longer a bottleneck to growth, or testing new channelsAnd ultimately, they were able to do more with less.Check out the full episode here.
97: Increasing Free Trial to Customer Conversion to 70% (w/ Jason Rozenblat, CallRail)
Jun 29 2022
97: Increasing Free Trial to Customer Conversion to 70% (w/ Jason Rozenblat, CallRail)
CallRail is an incredibly data-driven company. They transparently share performance metrics across the entire team, to foster accountability and ownership. By looking at the metrics regularly, they’re never surprised to see a low or high number at the end of the month. And they work together to try and identify negative (or positive) trends when they see them happening in real-time.In this episode, Jason Rozenblat (VP of Strategic Accounts) shares how CallRail grew Free Trial to Customer Conversion %: the percentage of total users who begin a free trial and end up becoming paid customers.While they have other metrics they obsess over (namely MRR, ARR, and ARPU), Jason and his team are especially focused on “Free Trial to Customer Conversion %”  because it directly impacts deal size and close rate.It’s also important, in that it’s a shared metric across the team. Jason works with the Demand Gen team to grow it, and it’s shared by any teams that touch the website because those teams also care about driving traffic and improving website conversion rate. The two go hand in hand.This includes engineering, product marketing, and customer marketing. So they obsess over this metric as an entire organization.How they grew itJason and his team found a number of things that have contributed to growing this metric.Changing from monthly to weekly cohorts.By measuring cohorts weekly rather than monthly, they were able to get much more granular and ask, “what happened this week, that was different than other weeks?”. This helped them spot causes of growth or decline in real-time, as opposed to waiting until the end of the month and looking at a post-mortem. They also started tracking cohorts in 5-week intervals (from 2-week intervals). Since they have a 2-week free trial, they used to analyze cohorts in 2-week intervals. But they started to realize that there was always a long tail of trials that would close way past the 2-week mark. Users would extend their free trials, or come back after a trial had expired in order to enter payment information. So by extending the sales cycle, and measuring cohorts in 5-week intervals, they got a clearer picture of what was going on and had better data to make decisions from.They changed the way they handled lead assignments.Before, if sales reps were going to be using PTO the following week, they’d be pulled out of rotation to ensure they weren’t assigned any new free trials to manage. But what they didn’t account for was all the free trials that were set to expire on while that rep would be out of office.So they changed the way they handled lead assignments, to make sure that whenever a free trial expired, it was passed off to a rep who would be in office during that time. They also started to view expired trials as viable leads and focused more on converting them.They focused on sales training and education.On top of all of this, they continued training sales reps on how to better handle objects, close deals, etc.ResultsThe results they saw were amazing. Some months, they increased their Free Trial to Customer Conversion rate as high as 10 points.With the traffic and free trial volume, they had at the time, that change alone could add an additional 100-150 customers or $100k of ARR.And in certain cohorts, they saw trial to conversion rates of 70-80%.View the full episode here.
96: Improving Website Conversion Rate by 6% (w/ Adam Goyette, Help Scout)
Jun 23 2022
96: Improving Website Conversion Rate by 6% (w/ Adam Goyette, Help Scout)
In this episode John Bonini chats with Adam Goyette, VP of Marketing at Help Scout, to learn how they grew their website conversion rate, and why that metric became a priority for the team.You’ll learn…How the Help Scout executive team sets annual goalsHow the marketing team identifies where to invest their time and moneyHow improving the website conversion rate became a priorityWhy Website Conversion Rate?Each year, the Help Scout executive team works together to identify what their annual revenue goal is, and what growth % they’re aiming to hit in the upcoming year.Once they have this number and growth %, they work backward to find how many signups and new customers they’ll need in order to hit that goal. Although the revenue goal is set annually, they’ll adjust the forecast of what they’re expecting quarter by quarter. This allows them to make smaller adjustments in real-time, as they see how things are trending.Transparently sharing their performanceEvery day, an email is delivered to the team, showing them how they’re progressing towards that month’s goal. It includes a breakdown of trials, sales opportunities, and projected MRR. On top of that, individual teams meet weekly to review their own numbers. And executive teams meet once a month, reviewing what happened in the last month and where they’re going next month. They feel that having the numbers transparently in front of the entire team, encourages everyone to be creative and offer up solutions to help improve that number. Looking for growth opportunitiesOnce they have their growth goals in place, it’s time to figure out how to achieve them. Their goal is to find the right set of “levers” to pull, in order to move the needle on traffic, free trials, demo requests, weighted pipeline, and more.And there are dozens of levers they could pull. It’s probably the same challenge you face at your company. Do you try new channels, or grow existing ones? Do you send more traffic, or improve conversion with the traffic you have? To help narrow things down, they look how each stage of their funnel is performing, and how each channel is performing. Then they ask questions like, “what channels can we reasonably expect to grow?” and “what channels might be worth investing in?”They also look for the easiest wins. For example, if paid channels are steeped in competition with deeper pockets, they’ll look for a channel where they can be more competitive. Or they might find they can get significant results just by doubling down on an existing channel.Why they chose Website Conversion RateAdam and the team found that the free trial to paid conversion rate was 20%+, which was already high for the industry. But if they looked higher up in the funnel, they found they were getting 500,000 visitors every month. They decided it would be far easier and more impactful for them to increase the website’s conversion rate (driving more free trial signups), than it would to increase an already high “trial to conversion rate” of 20%.So they set to work running experiments.How They Improved ItThey view their website content in 2 main buckets: “High-Intent Pages” and “Low-Intent Pages”.High intent pages include the homepage or product pages, where people are visiting with the intent to explore and potentially sign up for the product. Here, the call to action is “sign up” or “start free trial”. Low intent pages include content like a blog or thought leadership content, so they make the call to action something like “join the newsletter”. This encourages visitors to stay in the Help Scout ecosystem, without forcing them to take an action they have no intention of taking. When setting out to measure and improve their website conversion rate, they only looked at conversion on the “high intent pages”. This helped them get a more accurate number of how they were performing on pages that had a set call to action of conversion.Their current “website to free trial” conversion rate was 2% on those high intent pages, and their conversion rate from “free trial to active paying customer” was 20%. They assembled a “task force” of stakeholdersWebsite conversion is often “cross-functional”. In other words, it’s owned or used by multiple teams. Brand marketing might own the messaging. Product marketing might own the positioning. And growth marketing might own SEO or conversion rate.So Adam and the team put together an “optimization squad”, comprised of all the stakeholders who needed to have input on the website. This ensured that every stakeholder had seat at the table, and could work together on improving conversion without stepping on each other’s toes.They tested everythingThey experimented with just about everything. But they saw the biggest results by adding personalization. Helpscout has a wide base of customers, so by understanding who their buyers are, they’re able to present more helpful messaging tailored to those personas.For example, they found that smaller companies have to convert better by going through self-serve, while bigger companies almost always convert better when they speak with sales. The optimization squad would take an insight like this, and present a dynamic (changing) call to action, depending on the person viewing the site. Someone from a company with more than 500 employees might see “talk with sales” while someone from a small company sees “start free trial”. They’d also highlight different use cases of the product, and change the way they talked about Help Scout. For example, if a 500+ person organization read, “Help desk software for small business”, they might feel Help Scout wasn’t for them. By personalizing the team could show different customer logos (that looked like the visitor’s company), make the language more relevant, and be more helpful with use cases that visitor was interested in.In total, personalization included dynamically presenting the call to action, headlines, length of free trial, use cases and social proof.ResultsIn just 6 months, they saw a 56% increase in demo requests and a 6% increase in trials.Check out the episode summary here.