Social Selling Strategy: A Signal-Based Playbook with Laura Erdem

TL;DR

• Laura Erdem scaled Dreamdata from "close to no revenue" to $5M+ annually using a disciplined social selling strategy that treats LinkedIn as a qualification system, not a broadcast channel
• Define your ICP with surgical precision not "B2B marketers" but Directors/VPs of Marketing at B2B SaaS companies struggling with specific attribution and reporting problems
• Create content that addresses their daily problems, not your product features — 40% educational, 40% product marketing (customer journeys), 20% experimental
• Capture intent signals when they visit your website — use tools to track anonymous visitors and get Slack alerts when target accounts show buying behavior
• Initiate conversations only after establishing relevance — start human conversations based on their content engagement, never pitch immediately
• The average B2B SaaS customer journey takes 211 days from first touch to close — most companies only measure the last 60 days and miss where social selling does its highest-leverage work.
• This isn't about going viral, it's about becoming relevant to the right 500 people and knowing exactly when they're ready to buy

What Social Selling Actually Is (and Isn’t)

Most sales teams treat LinkedIn like a megaphone: push content, spray demos, chase vanity metrics. They're burning through reps, scorching their ICP, and wondering why their pipeline looks like a graveyard.

Laura Erdem took a different path. Five years ago, she left Gartner—a stable enterprise role—to join Dreamdata when it had "close to no revenue." Today, the company generates over $5 million annually, with 50% of revenue coming from the US market despite being European-based. The engine? A disciplined social selling strategy that treats LinkedIn not as a broadcast channel, but as a qualification and nurturing system that feeds a signal-based sales motion.

This isn't about going viral. It's about becoming relevant to the right 500 people, understanding when they're in-market, and starting conversations that don't feel like ambush tactics. What Erdem has built is a playbook that works precisely because it refuses to scale the parts that shouldn't be scaled.

Why Most B2B LinkedIn Marketing Fails Before It Starts

The first mistake companies make is treating social selling as a content problem. They hire writers, build calendars, chase trends. But trends are for audiences you don't want.

Erdem's framework starts with a single question: Who do you want to be relevant for?

Not "Who's on LinkedIn?" Not "Who might buy?" The specific persona, at the specific seniority level, dealing with specific daily problems. For Dreamdata, that's B2B SaaS marketers at the director or VP level—the people who feel the pain of attribution gaps and board-level reporting pressure. Not CMOs receiving polished decks. Not coordinators managing campaigns. The person in the middle, where the chaos lives.

This clarity changes everything. It determines:

• What you write about (measurement, hiring, content strategy—not product features)
• How you write it (entertaining enough to stop the scroll, specific enough to signal expertise)
• When you pitch (only after you've seen website visits, pricing page views, and feature exploration)

"If you're following trends, you're going to be relevant to nobody. Nobody will really care. Maybe you'll go viral once in a while, but this is irrelevant for the target that you are on LinkedIn for, which is most of the time revenue."
— Laura Erdem, Director of Global Sales, Dreamdata

"Marketers are a very hard crowd to sell to because they know how to do this thing," Erdem explains. They see through generic tactics instantly. So the content has to be genuinely useful before it's promotional.

Erdem posts five days a week: twice from podcast content, once showing a customer journey (product marketing), and twice on topics like ad performance or hiring. The customer journey posts—showing exactly how a client discovered and bought Dreamdata—perform exceptionally well, even though "it is not the most impactful feature of our product." It's visual, it's voyeuristic, and it answers the question marketers obsess over: What does good look like?

Why Content Calendars Kill Pipeline (And What to Do Instead)

Erdem doesn't use a content calendar. But she also kind of does.

When pressed, she admits there's a rhythm: two podcast-based videos, one customer journey, two original posts. But nothing's scheduled weeks in advance. There's no editorial board approving themes. The structure exists in her head because she's internalized what works.

This is critical. Most companies ossify too early. They template the creative work before they've learned what resonates. Erdem's approach is the opposite: test aggressively, find what gets engagement from your ICP specifically, then systematize execution without killing the voice.

Content-led pipeline generation requires this balance. You need enough consistency to stay top-of-mind, but enough flexibility to react to what's working now. Marketers scroll fast. Video stops them. Specific data (like B2B benchmarks for LinkedIn or Google ads) makes them lean in. Abstract thought leadership gets ignored.

And here's the contrarian part: Erdem doesn't care about likes from random people. She cares about comments from people at target accounts. Those comments become the entry point for relationship-building. But she never moves conversations into DMs immediately.

"Imagine this conversation in public in a normal group setting of people. Somebody asks you a question after a presentation and then you say, 'I'll get back to you directly.' No. When somebody asks something to you in public, you respond in public—because everyone else is watching that exchange."
— Laura Erdem

Why? Because everyone else watching that exchange is also evaluating your expertise. Answering publicly is performative in the best sense—it signals competence to dozens of lurkers who never comment themselves.

This principle mirrors what Max Mitcham demonstrates in his breakdown of Trigify's content-led funnel strategy using public conversations to build authority compounds faster than any gated content strategy.

How to Use Intent Signals to Turn LinkedIn Engagement Into Pipeline

Here's where Dreamdata's motion gets interesting. Social selling creates visibility. But visibility doesn't close deals. You need a trigger—a signal that someone's moved from passive consumption to active evaluation.

Setting Up Your Signal Capture System

Dreamdata uses its own product for this. When a target account hits the website, Erdem gets a Slack notification. Not just any visitor—companies she's manually flagged as high-priority. She can see if they're browsing pricing, product pages, or documentation. That's the cue to reach out.

But she doesn't pitch.

"I still don't know if that's the same person who goes into my website. But I know that this company is already looking into Dreamdata." So instead of a demo request, she starts a conversation. A human one. About attribution challenges, or hiring, or something contextually relevant based on what that person has engaged with on LinkedIn.

When to Reach Out (And What to Say)

This is the difference between cold outbound and signal-based outbound. Cold assumes nothing. Signal-based assumes curiosity. The message can be warmer, more specific, less transactional. And because the person has already seen Erdem's content—maybe even commented on it—the response rate is dramatically higher.

The magic happens when you start meaningful conversations in direct messages. "When you start conversations on LinkedIn and you've got the response from both sides, they will be exposed to your content even more," Erdem explains. LinkedIn's algorithm prioritizes content from people you've recently messaged with—a hidden advantage most people miss.

But the conversation can't be transactional. "It should not be like, 'Oh, I saw you liked this. Do you want to book a demo?' It's like freaking not, because it was just an interesting post for me. If you just start a conversation like a normal human being, they will start seeing your content even more."

Why 211 Days Matters for Pipeline Forecasting

Dreamdata's benchmark data shows the average B2B SaaS customer journey takes 211 days from first touch to closed deal. That's seven months of invisible research, dark social, and evaluation. According to Gartner's 2024 B2B Buying Journey research, enterprise software purchases now involve 6-10 stakeholders and 27 touchpoints on average—reinforcing why patient, multi-threaded engagement matters.

Most companies only measure from "lead created" to "deal closed"—maybe 60 days—and miss the entire top-of-funnel motion that made the conversion possible.

"Everything marketing does before they submit demos is insanely powerful, but you have to map it out to be able to know if I'm releasing a piece of content, it will probably take me several months to actually start seeing pipeline."
— Laura Erdem

This is why content calendars optimized for 30-day performance windows fail. If you're measuring success on monthly cycles, you're optimizing for the wrong outcome.

How to Convert LinkedIn Signals Into Booked Demos (Without Burning Bridges)

Once someone books a demo, the handoff matters. Dreamdata doesn't gate meetings behind SDRs. Inbound leads go straight to account executives—senior reps who can diagnose use cases, personalize demos, and disqualify fast.

"A win-win for having a senior AE speaking with your target audience instantly is from both sides. The buyer feels special because they are able to see the product tailored for them. On the other hand, if the use case is very niche and very likely we're not going to be able to work together, a senior AE would know."

This is counter to most SaaS playbooks, which treat SDRs as qualification filters. But Erdem's argument is that over-qualification burns trust. If someone has already navigated seven months of content, consumed interactive demos, and read benchmarks, they don't need a 15-minute "discovery" call with a junior rep. They need a technical conversation.

The social selling strategy creates the conditions for this efficiency. By the time someone requests a demo, they've self-qualified through content engagement, website behavior, and often direct LinkedIn conversations. The AE isn't starting cold—they're continuing a relationship that's been building for months.

This buyer enablement approach is similar to the principles Vukasin Vukosavljevic demonstrates in Heyreach's playbook for making inbound work reducing friction in high-intent moments by letting content do the heavy lifting.

Why Founder-Led Social Selling Generates 3x More Pipeline

One of the most striking elements of Dreamdata's approach is that "everybody's in sales." The CEO books demos. The CMO runs outbound. Erdem herself still takes meetings.

This isn't a bootstrapped-startup-doing-whatever-it-takes story. It's strategic. When a VP of Marketing at a high-priority account sees a message from Dreamdata's CEO, the signal is different. It's not just a sales rep following a cadence. It's a leadership-level conversation.

"Your buyers do want to hear from your leaders. And they are the easiest hype for you to create as well by trying to book meetings too."

But Erdem doesn't mandate that AEs post on LinkedIn. Personal branding is optional. Some reps are better at cold calling. Some prefer email. The key is that the system doesn't depend on everyone being a content creator. The system depends on:

1. Top-of-funnel visibility (created by a few high-output individuals like Erdem, the CEO, and CMO)
2. Signal capture (website behavior, LinkedIn engagement, intent data)
3. Thoughtful outreach (personalized, contextual, human)

This is a critical insight for companies trying to "scale" social selling. You can't scale authenticity by forcing 30 reps to post mediocre content. You can scale signal-based outreach by giving reps better data about who's in-market and what they care about.

This principle of role specialization is something Alina Vandenberghe demonstrates in her episode on orchestrating human-AI workflows at scale avoiding one-size-fits-all mandates and instead optimizing for individual strengths.

How to Use Ungated Content to Qualify Buyers Before They Book Demos

Most B2B content strategies treat gated assets as the goal. Download the ebook, submit the form, enter the funnel. Erdem's perspective is more nuanced.

Dreamdata does have gated content—B2B benchmarks for LinkedIn ads and Google ads perform exceptionally well. "Marketers are willing to give out their emails for that type of content because everybody wants to know, am I performing compared to the rest?"

But the majority of content is ungated. LinkedIn posts, podcast clips, customer journey visualizations—all accessible without friction. The goal isn't to capture emails. It's to build familiarity and signal intent through engagement patterns.

This aligns with Forrester's research on buyer self-education, which shows that B2B buyers complete 70% of their purchasing decision before ever engaging with sales. The ungated content is doing qualification work that used to require multiple discovery calls.

When someone comments on three posts, visits the website twice, and then downloads the benchmarks, that's a qualified signal. When someone just downloads the benchmarks, that's a data point.

This is the shift from demand capture to demand creation. You're not waiting for people to raise their hands. You're creating the conditions where raising a hand feels like the natural next step.

And critically, the content has to be good enough that people want to engage even when they're not buying. "If you did not spend time figuring out what you're going to write, write it in a different way and insightful, how a human would write it, why would I want to read it if it's created by AI?"

Erdem is blunt about AI-generated content: it's "crap in, crap out." Readers can tell. Engagement drops. The algorithm punishes it. Personal brand equity—the reason someone takes your call six months later—erodes.

The Tactical Breakdown: How to Build Your Own Social Selling Strategy

If you're a founder, marketer, or sales leader trying to replicate this, here's the operational playbook:

Step 1: Define Your ICP with Painful Specificity

Not "B2B marketers." Not "SaaS companies." The exact title, seniority, company size, and daily problem. For Dreamdata, that's Directors and VPs of Marketing at B2B SaaS companies struggling with attribution and board reporting.

Step 2: Audit What Your ICP Actually Engages With

Go to LinkedIn. Find 10 people who match your ICP. See what they post, comment on, and share. Don't guess. Don't use your own preferences. Marketers like to be entertained. CFOs don't. Engineers want depth. Operators want efficiency. Your content format must match their consumption behavior.

Step 3: Create a Content Rhythm (Not a Calendar)

Post consistently—five days a week is Erdem's cadence—but don't over-schedule. The rhythm should be:

• 40% educational/thought leadership (relevant to their daily work)
• 40% product marketing (customer stories, use cases, visual proof)
• 20% experimental (reactions, hot takes, process transparency)

Step 4: Build Signal Capture Infrastructure

Use intent tracking tools to identify anonymous website visitors from target accounts. Set up Slack alerts so your team gets notified when high-priority companies show buying behavior. Connect LinkedIn engagement data to your CRM. The goal is to know when someone moves from awareness to consideration—not just that they're aware of you.

Step 5: Design Outreach That Doesn't Feel Like Outreach

When you see signals, reach out with context. Reference a post they commented on. Ask about a challenge they mentioned. Offer a resource without asking for anything. The goal is to start a conversation, not close a deal.

Step 6: Let AEs Own the Close

Once someone books a demo, hand them to a senior rep who can personalize the conversation. Don't waste warm leads on qualification scripts. Trust that your content and signal capture already did the qualification work.

The systematic approach to content production Erdem describes is similar to the frameworks Adam Robinson applies in his edutainment-driven B2B growth playbook creating repeatable systems without losing creative edge.

Why AI Should Amplify Your Social Selling Strategy, Not Replace It

Erdem is cautiously optimistic about AI in content creation. Dreamdata uses AI agents to pull clips from podcasts and suggest post ideas for AEs who want to contribute but don't know where to start.

But there's a hard line: AI should identify, not generate.

"Nowadays when AI content is so easy to identify, it's good to encourage people to post it for the sake of now I'm out, like the bandaid is off and I'm able to do that over and over again. But I would encourage it a little faster for them to add in their own ideas, add in their own messaging so it does not feel too automated."

The workflow looks like this:

1. Record a podcast or demo call
2. Feed the transcript into an AI agent
3. Agent identifies 30 potential LinkedIn posts (quotes, frameworks, data points)
4. AE picks one, rewrites it in their voice, and posts

The AI handles the grunt work—transcription, segmentation, format suggestions. The human handles the judgment—what's interesting, what's on-brand, what matches the current sales narrative.

This is the future of personal brand building at scale. Not everyone has time to write five posts a week. But everyone can edit three sentences and hit "publish."

Edbound AI's podcast-to-content system automates this exact workflow—from recording to LinkedIn-ready clips—so you can execute Erdem's playbook without hiring a content team. Turn one podcast into 30+ LinkedIn posts automatically

Social Selling ROI: Why Year 2 Outperforms Paid Ads by 10x

If you spend $50K on LinkedIn ads, you'll generate leads immediately. Some will convert. Most will go cold. Next month, you spend another $50K. The cycle repeats.

If you invest that same $50K into building personal brands for three executives—coaching, content production, video editing—you'll see slower results in month one. But by month six, those executives have 15,000 combined followers. Their posts reach 100K impressions per month organically. Every new post amplifies past content. Every conversation builds on previous trust.

By year two, the paid ads are still costing $50K/month. The personal brands are generating pipeline for free.

This is why Erdem calls social selling a "long tail process." You're not optimizing for quarterly bookings. You're building an asset that compounds. Each post increases the chance that your next outbound message gets a response. Each comment deepens a relationship that might close in Q4 instead of Q2.

The companies that win are the ones willing to play the long game.

Social Selling Timeline: What to Expect Month by Month

"How long before I see pipeline from social selling?"

Realistic expectation: 4-6 months to first LinkedIn-sourced demo, 7-12 months to consistent pipeline.

"When should I give up on social selling?"

If you've posted 5x/week for 3 months with zero engagement from your ICP (not total engagement—ICP engagement), either:

1. Your ICP isn't actually on LinkedIn (rare)
2. Your content doesn't address their real problems (common)
3. You're optimizing for vanity metrics instead of relevance (very common)

Audit your last 20 posts: Are you talking about your product, or their problems?

What This Means for Content-Led Growth

Erdem's playbook isn't just about LinkedIn. It's about designing a GTM motion where content does three jobs:

1. Education (builds authority with your ICP)
2. Qualification (signals who's in-market based on engagement patterns)
3. Enablement (gives buyers the information they need to self-serve before booking demos)

This is the essence of content-led pipeline generation. You're not hoping people stumble onto your website. You're deliberately creating pathways—through LinkedIn, podcasts, benchmarks, customer stories—that guide high-intent buyers toward a conversation.

And critically, you're measuring which content drives pipeline. Dreamdata's own product showed them that certain blog posts were heavily consumed by deals in late-stage evaluation. Those posts weren't driving demo requests. They were driving closes. Without attribution data, the marketing team might have killed them.

"We were totally surprised by some of the pieces on our website are performing so well at the very end of the customer journey for closing new business. And we usually thought that nobody is actually reading them, but it was a totally different understanding."

This is the unlock. Most content strategies are judged by top-of-funnel metrics—views, downloads, MQLs. But the content that matters often lives deeper in the funnel, shortening sales cycles and increasing close rates.

If This Resonates, Here's What to Do Next

Laura Erdem spent five years building a social selling strategy that generates millions in pipeline using clarity, consistency, and a system that knows when to scale and when to stay human—the same principles leaders like Scott Leese applies in his systems-driven approach to building million-dollar pipelines.

If you're a founder or marketing leader trying to build something similar, the challenge isn't strategy. It's execution. Posting five days a week. Tracking signals across multiple tools. Coordinating outreach with sales. Repurposing content without burning out.

That's where Edbound AI comes in. We help you operationalize the entire content-led motion—from podcast recording to LinkedIn distribution to signal-based outreach—without adding headcount. Think of it as the infrastructure that lets you execute Erdem's playbook at scale, consistently, without sacrificing the human judgment that makes it work.

If you want to turn your expertise into a pipeline the way Dreamdata does, let's talk. 

Start building your content-led engine with Edbound AI.

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