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The Current State of Google’s Search Generative Experience [What It Means for SEO in 2024]

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By Tinuiti Team

SEO enthusiasts, known for naming algorithm updates after animals and embracing melodrama, find themselves in a landscape where the “adapt or die” mantra prevails. So when Google announced the launch of its Search Generative Experience (SGE) in May of 2023 at Google/IO, you can imagine the reaction was immense.

Although SGE has the potential to be a truly transformative force in the landscape, we’re still waiting for SGE to move out of the Google Labs Sandbox and integrate into standard search results. 

Curious about our current take on SGE and its potential impact on SEO in the future? Read on for more.

Decoding Google’s Defensive Move

In response to potential threats from competitors like ChatGPT, Bing, TikTok, Reddit, and Amazon, Google introduced SGE as a defensive maneuver. However, its initial beta release raised questions about its readiness and global deployment.

ChatGPT provided an existential threat that had the potential to eat into Google’s market share. When Bing started incorporating it into its search results, it was one of the most significant wins for Bing in a decade. In combination with threats from TikTok, Reddit, and Amazon, we see a more fractured search landscape less dominated by Google. Upon its launch, the expectation was that Google would push its SGE solution globally, impact most queries, and massively shake up organic search results and strategies to improve organic visibility.

Now, industry leaders are starting to question if Google is better off leaving SGE in the testing ground in Google labs. According to Google’s recent update, it appears that SGE will remain an opt-in experience in Google Labs (for at least the short term). If SGE was released, there could be a fundamental reset in understanding SEO. Everything from organic traffic to optimization tactics to tracking tools would need adjustments for the new experience. Therefore, the prospect of SGE staying in Google Labs is comforting if not entirely reliable. 

The ever-present option is that Google can change its mind at any point and push SGE out broadly as part of its standard search experience. For this reason, we see value in learning from our observations with SGE and continuing to stay on top of the experience.

SGE User Experience and Operational Challenges

If you’ve signed up for search labs and have been experimenting with SGE for a while, you know firsthand there are various issues that Google should address before rolling it out broadly to the public.

At a high level, these issues fall into two broad categories including user experience issues and operational issues.

Below are some significant issues we’ve come across, with Google making notable progress in addressing certain ones, while others still require improvement:

  • Load time – Too many AI-generated answers take longer to load than a user is willing to wait. Google recommends less than a 3-second load time to meet expectations. They’ll need to figure out how to consistently return results quickly if they want to see a higher adoption rate.
  • Layout – The SGE layout is massive. We believe any major rollout will be more streamlined to make it a less intrusive experience for users and allow more visibility for ads, and if we’re lucky, organic results. Unfortunately, there is still a decent chance that organic results will move below the fold, especially on mobile devices. Recently, Google has incorporated more results where users are prompted to generate the AI result if they’d like to see it. The hope is Google makes this the default in the event of a broad rollout where users can generate an AI result if they want one instead of assuming that’s what a user would like to see. 
  • Redundancy – The AI result duplicates features from the map pack and quick answer results. 
  • Attribution – Due to user feedback, Google includes sources on several of their AI-powered overviews where you can see relevant web pages if there is an arrow next to the result. Currently, the best way to appear as one of these relevant pages is to be one of the top-ranked results, which is convenient from an optimization standpoint. Changes to how attribution and sourcing are handled could heavily impact organic strategies. 

On the operational side, Google also faces significant hurdles to making SGE a viable product for its traditional search product. The biggest obstacle appears to be making the cost associated with the technology worth the business outcomes it provides. If this was a necessary investment to maintain market share, Google might be willing to eat the cost, but if their current position is relatively stable, Google doesn’t have much of an incentive to take on the additional cost burden of heavily leveraging generative AI while also presumably taking a hit to their ad revenue. Especially since slow user adoption doesn’t indicate this is something users are demanding at the moment.

While the current experience of SGE is including ads above the generative results now, the earliest iterations didn’t heavily feature sponsored ads. While they are now included, the current SGE layout would still significantly disrupt the ad experience we’re used to. During the Google I/O announcement, they made a statement to reassure advertisers they would be mindful of maintaining a distinct ad experience in search.  

“In this new generative experience, Search ads will continue to appear in dedicated ad slots throughout the page. And we’ll continue to uphold our commitment to ads transparency and making sure ads are distinguishable from organic search results” – Elizabeth Reid, VP, Search at Google

Google is trying to thread a delicate needle here of staying on the cutting edge with their search features, while trying not to upset their advertisers and needlessly hinder their own revenue stream. Roger Montti details more of the operational issues in a recent article digging into the surprising reasons SGE is stuck in Google Labs.

He lists three big problems that need to be solved before SGE will be integrated into the foreground of search:

  1. Large Language Models being inadequate as an information retrieval system
  2. The inefficiency and cost of transformer architecture
  3. Hallucinating (providing inaccurate answers)

Until SGE provides more user value and checks more boxes on the business sense side, the traditional search experience is here to stay. Unfortunately, we don’t know when or if Google will ever feel confident they’ve addressed all of these concerns, so we’ll need to stay prepared for change.

Experts Chime in on Search Generative Experience

Our team has been actively engaging with SGE, here’s a closer look at their thoughts and opinions on the experience so far:

“With SGE still in its early stages, I’ve noticed consistent changes in how the generative results are produced and weaved naturally into the SERPs. Because of this, I feel it is imperative to stay on top of these on-going changes to ensure we can continue to educate our clients on what to expect when SGE is officially incorporated into our everyday lives. Although an official launch date is currently unknown, I believe proactively testing various prompt types and recording our learnings is important to prepare our clients for this next evolution of Google search.”

– Jon Pagano, SEO Sr. Specialist at Tinuiti

“It’s been exciting to watch SGE grow through different variations over the last year, but like other AI solutions its potential still outweighs its functionality and usefulness. What’s interesting to see is that SGE doesn’t just cite its sources of information, but also provides an enhanced preview of each webpage referenced. This presents a unique organic opportunity where previously untouchable top 10 rankings are far more accessible to the average website. Time will tell what the top ranking factors for SGE are, but verifiable content with strong E-E-A-T signals will be imperative.”

–Kate Fischer, SEO Specialist at Tinuiti

“Traditionally, AI tools were very good at analytical tasks. With the rise of ChatGPT, users can have long-form, multi-question conversations not yet available in search results. When, not if, released, Google’s Generative Experience will transform how we view AI and search. Because there are so many unknowns, some of the most impactful ways we prepare our clients are to discover and develop SEO strategies that AI tools can’t directly disrupt, like mid to low funnel content.”

– Brandon Miller, SEO Specialist at Tinuiti

“SGE is going to make a huge impact on the ecommerce industry by changing the way users interact with the search results. Improved shopping experience will allow users to compare products, price match, and read reviews in order to make it quicker and easier for a user to find the best deals and purchase. Although this leads to more competitive results, it also improves organic visibility and expands our product reach. It is more important than ever to ensure all elements of a page are uniquely and specifically optimized for search. With the SGE updates expected to continue to impact search results, the best way to stay ahead is by focusing on strong user focused content and detailed product page optimizations.” 

– Kellie Daley, SEO Sr. Specialist at Tinuiti

Navigating the Clash of Trends

One of the most interesting aspects of the generative AI trend in search is that it appears to be in direct opposition to other recent trends.

One of the ways Google has historically evaluated the efficacy of its search ranking systems is through the manual review of quality raters. In their quality rater guidelines, raters were instructed to review for things like expertise, authority, and trustworthiness (EAT) in results to determine if Google results are providing users the information they deserve. 

In 2022, Google updated their search guidelines to include another ‘e’ in the form of experience (EEAT). In their words, Google wanted to better assess if the content a user was consuming was created by someone with, “a degree of experience, such as with actual use of a product, having actually visited a place or communicating what a person has experienced. There are some situations where really what you value most is content produced by someone who has firsthand, life experience on the topic at hand.” 

Generative AI results, while cutting-edge technology and wildly impressive in some cases, stand in direct opposition to the principles of E-E-A-T. That’s not to say that there’s no room for both in search, but Google will have to determine what it thinks users value more between these competing trends. The slow adoption of SGE could be an indication that a preference for human experience, expertise, authority, and trust is winning round one in this fight. 

Along these lines, Google is also diversifying its search results to cater to the format in which users get their information. This takes the form of their Perspectives Filter. Also announced at Google I/O 2023, the perspectives filter incorporates more video, image, and discussion board posts from places like TikTok, YouTube, Reddit, and Quora. Once again, this trend shows the emphasis and value searchers place on experience and perspective. Users value individual experience over the impersonal conveyance of information. AI will never have these two things, even if it can provide a convincing imitation.

The current iteration of SGE seems to go too far in dismissing these trends in favor of generative AI. It’s an interesting challenge Google faces. If they don’t determine the prevailing trend correctly, veering too far in one direction can push more market share to ChatGPT or platforms like YouTube and TikTok.

Final Thoughts

The range of outcomes remains broad and fascinating for SGE. We can see this developing in different ways, and prognostication offers little value, but it’s invaluable to know the potential outcomes and prepare for as many of them as possible.

It’s critical that you or your search agency be interacting and experimenting with SGE because:

  • The format and results will most likely continue to see significant changes
  • This space moves quickly and it’s easy to fall behind
  • Google may fix all of the issues with SGE and decide to push it live, changing the landscape of search overnight
  • SGE experiments could inform other AI elements incorporated into the search experience

Ultimately, optimizing for the specific SGE experience we see now is less important because we know it will inevitably continue changing. We see more value in recognizing the trends and problems Google is trying to solve with this technology. With how quickly this space moves, any specifics mentioned in this article could be outdated in a week. That’s why focusing on intention and process is important at this stage of the game.

By understanding the future needs and wants SGE is attempting to address, we can help you future-proof your search strategies as much as possible. To some extent we’re always at the whims of the algorithm, but by maintaining a user-centric approach, you can make your customers happy, regardless of how they find you.

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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A deeper dive into data, personalization and Copilots

Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.

To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.

Dig deeper: Salesforce piles on the Einstein Copilots

Salesforce’s evolving architecture

It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?

“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”

Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”

That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.

“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.

Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”

Let’s learn more about Einstein Copilot

“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.

For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”

Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”

It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”

What’s new about Einstein Personalization

Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?

“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”

Finally, trust

One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.

“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”

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Why The Sales Team Hates Your Leads (And How To Fix It)

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Why The Sales Team Hates Your Leads (And How To Fix It)

Why The Sales Team Hates Your Leads And How To

You ask the head of marketing how the team is doing and get a giant thumbs up. 👍

“Our MQLs are up!”

“Website conversion rates are at an all-time high!”

“Email click rates have never been this good!”

But when you ask the head of sales the same question, you get the response that echoes across sales desks worldwide — the leads from marketing suck. 

If you’re in this boat, you’re not alone. The issue of “leads from marketing suck” is a common situation in most organizations. In a HubSpot survey, only 9.1% of salespeople said leads they received from marketing were of very high quality.

Why do sales teams hate marketing-generated leads? And how can marketers help their sales peers fall in love with their leads? 

Let’s dive into the answers to these questions. Then, I’ll give you my secret lead gen kung-fu to ensure your sales team loves their marketing leads. 

Marketers Must Take Ownership

“I’ve hit the lead goal. If sales can’t close them, it’s their problem.”

How many times have you heard one of your marketers say something like this? When your teams are heavily siloed, it’s not hard to see how they get to this mindset — after all, if your marketing metrics look strong, they’ve done their part, right?

Not necessarily. 

The job of a marketer is not to drive traffic or even leads. The job of the marketer is to create messaging and offers that lead to revenue. Marketing is not a 100-meter sprint — it’s a relay race. The marketing team runs the first leg and hands the baton to sales to sprint to the finish.

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via GIPHY

To make leads valuable beyond the vanity metric of watching your MQLs tick up, you need to segment and nurture them. Screen the leads to see if they meet the parameters of your ideal customer profile. If yes, nurture them to find out how close their intent is to a sale. Only then should you pass the leads to sales. 

Lead Quality Control is a Bitter Pill that Works

Tighter quality control might reduce your overall MQLs. Still, it will ensure only the relevant leads go to sales, which is a win for your team and your organization.

This shift will require a mindset shift for your marketing team: instead of living and dying by the sheer number of MQLs, you need to create a collaborative culture between sales and marketing. Reinforce that “strong” marketing metrics that result in poor leads going to sales aren’t really strong at all.  

When you foster this culture of collaboration and accountability, it will be easier for the marketing team to receive feedback from sales about lead quality without getting defensive. 

Remember, the sales team is only holding marketing accountable so the entire organization can achieve the right results. It’s not sales vs marketing — it’s sales and marketing working together to get a great result. Nothing more, nothing less. 

We’ve identified the problem and where we need to go. So, how you do you get there?

Fix #1: Focus On High ROI Marketing Activities First

What is more valuable to you:

  • One more blog post for a few more views? 
  • One great review that prospective buyers strongly relate to?

Hopefully, you’ll choose the latter. After all, talking to customers and getting a solid testimonial can help your sales team close leads today.  Current customers talking about their previous issues, the other solutions they tried, why they chose you, and the results you helped them achieve is marketing gold.

On the other hand, even the best blog content will take months to gain enough traction to impact your revenue.

Still, many marketers who say they want to prioritize customer reviews focus all their efforts on blog content and other “top of the funnel” (Awareness, Acquisition, and Activation) efforts. 

The bottom half of the growth marketing funnel (Retention, Reputation, and Revenue) often gets ignored, even though it’s where you’ll find some of the highest ROI activities.

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Most marketers know retaining a customer is easier than acquiring a new one. But knowing this and working with sales on retention and account expansion are two different things. 

When you start focusing on retention, upselling, and expansion, your entire organization will feel it, from sales to customer success. These happier customers will increase your average account value and drive awareness through strong word of mouth, giving you one heck of a win/win.

Winning the Retention, Reputation, and Referral game also helps feed your Awareness, Acquisition, and Activation activities:

  • Increasing customer retention means more dollars stay within your organization to help achieve revenue goals and fund lead gen initiatives.
  • A fully functioning referral system lowers your customer acquisition cost (CAC) because these leads are already warm coming in the door.
  • Case studies and reviews are powerful marketing assets for lead gen and nurture activities as they demonstrate how you’ve solved identical issues for other companies.

Remember that the bottom half of your marketing and sales funnel is just as important as the top half. After all, there’s no point pouring leads into a leaky funnel. Instead, you want to build a frictionless, powerful growth engine that brings in the right leads, nurtures them into customers, and then delights those customers to the point that they can’t help but rave about you.

So, build a strong foundation and start from the bottom up. You’ll find a better return on your investment. 

Fix #2: Join Sales Calls to Better Understand Your Target Audience

You can’t market well what you don’t know how to sell.

Your sales team speaks directly to customers, understands their pain points, and knows the language they use to talk about those pains. Your marketing team needs this information to craft the perfect marketing messaging your target audience will identify with.

When marketers join sales calls or speak to existing customers, they get firsthand introductions to these pain points. Often, marketers realize that customers’ pain points and reservations are very different from those they address in their messaging. 

Once you understand your ideal customers’ objections, anxieties, and pressing questions, you can create content and messaging to remove some of these reservations before the sales call. This effort removes a barrier for your sales team, resulting in more SQLs.

Fix #3: Create Collateral That Closes Deals

One-pagers, landing pages, PDFs, decks — sales collateral could be anything that helps increase the chance of closing a deal. Let me share an example from Lean Labs. 

Our webinar page has a CTA form that allows visitors to talk to our team. Instead of a simple “get in touch” form, we created a drop-down segmentation based on the user’s challenge and need. This step helps the reader feel seen, gives them hope that they’ll receive real value from the interaction, and provides unique content to users based on their selection.

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So, if they select I need help with crushing it on HubSpot, they’ll get a landing page with HubSpot-specific content (including a video) and a meeting scheduler. 

Speaking directly to your audience’s needs and pain points through these steps dramatically increases the chances of them booking a call. Why? Because instead of trusting that a generic “expert” will be able to help them with their highly specific problem, they can see through our content and our form design that Lean Labs can solve their most pressing pain point. 

Fix #4: Focus On Reviews and Create an Impact Loop

A lot of people think good marketing is expensive. You know what’s even more expensive? Bad marketing

To get the best ROI on your marketing efforts, you need to create a marketing machine that pays for itself. When you create this machine, you need to think about two loops: the growth loop and the impact loop.

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  • Growth loop — Awareness ➡ Acquisition ➡ Activation ➡ Revenue ➡ Awareness: This is where most marketers start. 
  • Impact loop — Results ➡ Reviews ➡ Retention ➡ Referrals ➡ Results: This is where great marketers start. 

Most marketers start with their growth loop and then hope that traction feeds into their impact loop. However, the reality is that starting with your impact loop is going to be far more likely to set your marketing engine up for success

Let me share a client story to show you what this looks like in real life.

Client Story: 4X Website Leads In A Single Quarter

We partnered with a health tech startup looking to grow their website leads. One way to grow website leads is to boost organic traffic, of course, but any organic play is going to take time. If you’re playing the SEO game alone, quadrupling conversions can take up to a year or longer.

But we did it in a single quarter. Here’s how.

We realized that the startup’s demos were converting lower than industry standards. A little more digging showed us why: our client was new enough to the market that the average person didn’t trust them enough yet to want to invest in checking out a demo. So, what did we do?

We prioritized the last part of the funnel: reputation.

We ran a 5-star reputation campaign to collect reviews. Once we had the reviews we needed, we showcased them at critical parts of the website and then made sure those same reviews were posted and shown on other third-party review platforms. 

Remember that reputation plays are vital, and they’re one of the plays startups often neglect at best and ignore at worst. What others say about your business is ten times more important than what you say about yourself

By providing customer validation at critical points in the buyer journey, we were able to 4X the website leads in a single quarter!

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So, when you talk to customers, always look for opportunities to drive review/referral conversations and use them in marketing collateral throughout the buyer journey. 

Fix #5: Launch Phantom Offers for Higher Quality Leads 

You may be reading this post thinking, okay, my lead magnets and offers might be way off the mark, but how will I get the budget to create a new one that might not even work?

It’s an age-old issue: marketing teams invest way too much time and resources into creating lead magnets that fail to generate quality leads

One way to improve your chances of success, remain nimble, and stay aligned with your audience without breaking the bank is to create phantom offers, i.e., gauge the audience interest in your lead magnet before you create them.

For example, if you want to create a “World Security Report” for Chief Security Officers, don’t do all the research and complete the report as Step One. Instead, tease the offer to your audience before you spend time making it. Put an offer on your site asking visitors to join the waitlist for this report. Then wait and see how that phantom offer converts. 

This is precisely what we did for a report by Allied Universal that ended up generating 80 conversions before its release.

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The best thing about a phantom offer is that it’s a win/win scenario: 

  • Best case: You get conversions even before you create your lead magnet.
  • Worst case: You save resources by not creating a lead magnet no one wants.  

Remember, You’re On The Same Team 

We’ve talked a lot about the reasons your marketing leads might suck. However, remember that it’s not all on marketers, either. At the end of the day, marketing and sales professionals are on the same team. They are not in competition with each other. They are allies working together toward a common goal. 

Smaller companies — or anyone under $10M in net new revenue — shouldn’t even separate sales and marketing into different departments. These teams need to be so in sync with one another that your best bet is to align them into a single growth team, one cohesive front with a single goal: profitable customer acquisition.

Interested in learning more about the growth marketing mindset? Check out the Lean Labs Growth Playbook that’s helped 25+ B2B SaaS marketing teams plan, budget, and accelerate growth.


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