Cold outbound data on 40M startups. Here's what works. | Landbase

Executive summary

Daniel Saks argues that product–market fit and outbound effectiveness are ongoing, segment-by-segment disciplines—not milestones a company reaches once. The strongest growth comes from finding a focused beachhead where customers show clear pull, proving value there, and expanding into adjacent markets.

For outbound, his central recommendation is to prioritize relevance over volume: build a detailed, continuously updated view of the total addressable market (TAM), identify the right companies and people, and match them with a credible, specific value proposition. Use automation to handle research and list-building, while reserving human sellers’ time for calls, meetings, and high-value accounts.

Business strategy and lessons

Product–market fit as “magnetic momentum”

• Saks describes product–market fit as a sense of pull: winning one influential customer creates interest from others who want a similar outcome.
• AppDirect used this approach to expand from Bell Canada to other telecoms, including AT&T, Comcast, and Deutsche Telekom. Later, it applied the same beachhead strategy in new sectors, such as IoT and manufacturing.
• Look for a “digital hero”—an influential early adopter whose successful use of a product can persuade others and advance that person’s career.
• Treat fit as specific to a customer segment. A company should keep testing and re-establishing fit as it enters new niches or adds products.

AppDirect: a beachhead is not enough

AppDirect’s original vision was to enable B2B companies, including telecoms, to resell SaaS and other business services through marketplaces.

Bell Canada had a large base of business customers, but the launch of its app store attracted little traffic despite ambitious promotion and a successful on-time launch. Saks attributed the failure in part to:

• Selling products that did not fit the trust and expertise customers associated with the telecom.
• Assuming that advertising would drive buyers to the store, rather than activating existing sales relationships.

The team adjusted its merchandising strategy and trained telecom salespeople to explain and sell relevant offerings. Saks said later launches at Deutsche Telekom and AT&T were more successful.

Takeaway: A distribution partner’s brand and customer base do not automatically create demand. Product selection and channel enablement must fit the buyer’s expectations.

Leadership and company transition

Saks moved from co-CEO at AppDirect to board member as co-founder Nicholas took over as CEO, allowing Saks to start Landbase. He framed the transition as a deliberate decision to give the mature company a single CEO while pursuing a new opportunity in agentic AI.

Landbase was founded around the view that AI capable of taking action—not just generating content—could transform business workflows, particularly sales and marketing.

Outbound playbook and frameworks

Map the TAM before launching outbound

• Identify segments, target companies, and relevant people—not just a broad industry label.
• Use customer and call records, CRM data, win/loss information, the company website, and competitor research to refine the map.
• Keep the map “living”: track which accounts have been reached, responses, objections, competitor relationships, and timing for future follow-up.
• A precise TAM map can inform prioritization, pipeline forecasting, market penetration, and decisions about adjacent markets.

Prioritize accounts and seller time

• Score and tier accounts. Saks described putting senior, founder-led effort into the most strategic accounts, assigning the team to the next tier, and automating lighter-touch outreach to lower tiers.
• Within a large account, identify the specific sponsor and relevant people on the ground. Job titles alone may not reveal who owns the problem.
• For top accounts, invest in tailored research and materials—such as a customized business case, pilot, landing page, or analysis of the account’s addressable market.

Make outreach specific and credible

• Aim for the right person, company, time, and value proposition.
• Use relevant customer examples and concise case studies to show how similar organizations benefited.
• Support outreach with an authentic digital presence. Prospects may look up the sender or company before responding.
• Use multiple channels—email, phone, LinkedIn, and, for high-value accounts, events or in-person meetings. Earlier touches can make a later call feel more familiar.

Automate research; keep people focused on selling

• Saks’s view is that the value of AI is not merely automating every SDR task. It is combining a company’s own data with external data to determine whom to contact and why.
• Automation can reduce manual list-building and research, allowing salespeople to spend more time calling and meeting qualified prospects.
• He cautioned against relying on generic, high-volume AI-generated outreach. Poor targeting can lead to spam complaints and damaged deliverability.

Experiment before scaling

• Treat outbound like product–market fit: early choices of audience, message, or channel may be wrong.
• Test at low volume, learn from results, and improve the targeting and value proposition before scaling.
• Saks advised startups not to launch outbound until prospects can look up the company and find credible evidence of its value.

Sequence outreach with restraint

• Use a coordinated sequence across channels rather than repeated messages on one channel.
• Saks said testing indicated that about three touches captured roughly 90% of the result. A fourth may be reasonable with a strong message, while five can increase the risk of spam flags.
• After an initial sequence, revisit engaged prospects sooner and let the rest go dormant—potentially for a quarter—before retrying, depending on the market and sales cycle.

Landbase and go-to-market approach

• Landbase combines company and contact data with AI-assisted research, prioritization, messaging, and outbound workflows.
• Saks said its platform draws on information about 40 million businesses, 400 million business profiles, and approximately 1,500 fields per area that can be used as signals.
• He described Landbase as being designed for AI agents to reason over data, including a customer’s CRM and other internal information, rather than requiring a specialist to manually build workflows.
• Saks contrasted three approaches:
  • Traditional data tools: Users filter within one vendor’s interface and build lists manually.
  • Clay-style workflows: Users combine multiple data sources, manipulate and validate the data, then send it to other tools; this can require technical GTM expertise.
  • Landbase’s approach: Agents use company data and customer context to identify and score accounts, recommend outreach, and surface suggested calls and contact details.
• Saks said Landbase can automate email and LinkedIn outreach and supports a dialer, but not automated voice calling because of regulatory hurdles.
• Saks described a benchmarking exercise comparing list precision across Landbase, Apollo, ZoomInfo, and Clay, and said Landbase’s precision was more than 2× the alternatives tested. This was a company-reported result, not an independently verified finding in the interview.

Metrics and figures cited

• Outbound email response rate: Saks estimated about 2% even for a good list in current conditions; a tightly targeted list may reach 8–10%. He speculated that highly recognized brands with heavily customized outreach might reach around 20%, but said this was rare.
• Phone connect rate: He cited 8–10% as a strong rate and said some companies start near 2%. He reported that better targeting had produced 2×–4× connect-rate improvements for some users, including fractional SDRs.
• Meeting and campaign efficacy: Saks said Landbase’s early model, GTM1 Omni, showed a claimed 4×–7× uplift in outbound campaign efficacy. He also cited 2×–4× improvements in connect rates and meetings booked across its network; these are speaker-reported results.
• Sales team time: Saks said SDRs at some companies spent about 35% of their time on manual list-building. He also characterized many reps’ time as split among research, email, and LinkedIn, leaving insufficient focus on calling.
• Outreach cadence: About three touches reportedly delivered 90% of the sequence’s result; five could add some benefit but raised spam risk.
• AppDirect scale: Saks said AppDirect’s customers’ marketplace transactions now represent upwards of $10 billion in gross merchandise value (GMV). He said it took roughly five to seven years to get the GMV flywheel working.
• AppDirect customer reach: Bell had about 500,000 business customers in Canada; AT&T had about 4 million in the U.S. Saks also said AppDirect had more than 10,000 agents/resellers.

Concrete recommendations

1. Start with the segment where the product has the clearest proof of value, not the broadest possible market.
2. Build and maintain a TAM map with named accounts, relevant buyers, priorities, and outreach history.
3. Reserve high-effort, personalized selling for the accounts with the greatest strategic value.
4. Use customer evidence and clear business cases to establish relevance and trust.
5. Build the sender’s and company’s public credibility before scaling cold outreach.
6. Test targeting, message, and channel combinations at low volume; scale only after results show genuine pull.
7. Use email and LinkedIn to support calling, rather than assuming digital messages alone are the strongest channel.
8. Reassess outbound continuously. If it is not working, investigate audience, buyer, value proposition, competition, and market saturation before increasing volume.

Presenters and sources

• Daniel Saks — co-founder of AppDirect and founder of Landbase; interview guest.
• Pablo — host/interviewer of the Product Market Fit Show.
• Source: Product Market Fit Show interview, “Cold outbound data on 40M startups. Here’s what works. | Landbase.”