David Patterson-Cole works on systems for outbound sales to small and midsize businesses. His posts focus on improving cold-call volume and decision-maker connections through data, targeting algorithms, and sales software.
Useful for practitioner-led content on making SMB outbound sales more productive through data, targeting, and sales systems.
Best for
A B2B sales technology company selling a dialer, sales-engagement tool, or SMB contact-data product.
Not for
A consumer brand or broad-reach B2B brand wanting large audience scale or off-the-shelf packages.
Key takeaways
An average SMB rep dials about 50 times a day.
Teams can reliably double that within a week; trained reps peaked above 300 dials.
Reps need 15 or more decision-maker connects a day, with 30 as gold standard.
Check first: Ask for audience demographics by role, seniority, industry, and geography plus collaboration terms and pricing.
Main ideas
Increase call volume before betting on better conversion · Diagnose outbound as volume, connects, and conversion · Make decision-maker conversations a daily operating target
They break outbound performance into volume, decision-maker connect rate, and conversion, with a different operational lever for each: reduce manual research, improve contact data and call timing, and qualify and route accounts more carefully.
They argue that volume is often the easiest lever to move, but not a cure on its own: their diagnostic framework calls for improving all three.
The Next Best Dial example shows how targeting could account for business type, time of day, prior attempts, and pickup history—a bar and a bakery may be best called at different times.
Across five posts, Patterson-Cole argues that SMB outbound works best as an operating system, not a single clever targeting trick.
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They prioritize enough calls and decision-maker conversations, then use data, timing, software, and qualification to make that activity more productive.
Their examples include performance claims about DataLane Deployed and an algorithm still being built.
Ask for independent verification of the performance claims.
Increase call volume before betting on better conversion
Teams often focus on signals and conversion, Patterson-Cole says, but conversion is harder to improve than call volume.
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They argue that higher volume should come before relying on better targeting alone.
Patterson-Cole puts the average SMB rep at about 50 dials a day, says that volume can double within a week, and says reps they trained peaked above 300. They also refer to a rough model in which a conversion lift has little effect on closed-won revenue without more volume.
Diagnose outbound as volume, connects, and conversion
More calls are not the whole answer.
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Patterson-Cole breaks cold-call-heavy outbound into three parts: volume, the rate of reaching decision-makers, and conversion. They recommend tackling friction in each part rather than looking for one fix.
Examples include removing manual account research to free up selling time, improving decision-maker phone data and call timing, and disqualifying poor-fit accounts or routing them to a better-matched rep.
Make decision-maker conversations a daily operating target
Patterson-Cole treats decision-maker connects as a key measure of whether SMB outbound is working.
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They argue that effective outbound can be a competitive advantage: more conversations and revenue give a company room to reinvest.
Patterson-Cole sets a benchmark of 15 or more decision-maker connects a day, calls 30 or more the new gold standard, and contrasts both with teams getting 5–7. Ask how these stated benchmarks were established.
Use data to choose which business to call, and when
Patterson-Cole’s targeting idea goes beyond selecting promising accounts: software should also help choose the best time to call, using business type and call history.
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They want the system to handle that analysis so reps can focus on conversations.
Patterson-Cole describes Next Best Dial as a system built to rank accounts by predicted decision-maker connect rates.
A bar, bakery, and lunch-serving restaurant may have different useful call windows; the model also considers attempts, pickup history, and role.
Ask for measured results before weighing the plan’s impact.
Build a connected sales system, not a standalone tool
In describing DataLane Deployed, Patterson-Cole links account data, targeting algorithms, purpose-built software, and experienced sales staff.
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They emphasize how the pieces work together to increase rep productivity, rather than presenting a data product alone.
Patterson-Cole says one rep booked 17 demos in a week while reps averaged more than 200 dials a day.
They list a frequently refreshed graph of 20 million-plus SMB accounts, algorithms including Next Best Dial and DM Boost, and Flow software built for SMB selling.
These are claims in their post about their company’s system.
Answers a practical question for SMB outbound teams: should they focus on better signals and conversion, or on making more calls?
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Start here for the volume-first argument that the other posts build on.
Argues that teams focus too much on signals and conversion when the bigger opportunity is volume, especially cold-call dials.
Patterson-Cole says conversion is hard to improve — teams struggle to lift it by more than 50% across their addressable market — while call volume is easier to shift.
They cite a concrete baseline: the average SMB rep dials around 50 times a day, teams can reliably double that within a week, and internally trained reps peaked above 300 dials in a day.
The post also references a rough revenue model showing that a conversion lift barely moves closed-won revenue without a matching volume increase.
For brands planning a campaign
For a sales technology company, this supports a campaign built around daily dial volume and reducing research friction before selling signal-selection tools. It can anchor a volume-first pilot or a comparison with signal-led platforms.
Offers a simple diagnostic model for why SMB outbound programs are unprofitable, breaking the problem into three parts a brand can test.
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Start here to see how Patterson-Cole frames the system before exploring individual tactics.
Says many SMB outbound programs are still unprofitable and reduces the motion to a formula: volume × connect rate × conversion.
The post lists common failures at each stage.
On volume, reps do not dial enough, and manual research between accounts can add more than an hour of non-selling time a day.
On connect rate, reps spend too little time talking to decision makers, making better mobile numbers and call timing important.
On conversion, reps talk to accounts that will never close; teams should disqualify more, score for fit, and route accounts to the reps most likely to close them.
The post says there is no silver bullet and cites an organization adding more than $1m ARR per rep as a best-in-class example.
For brands planning a campaign
A campaign can use this three-part diagnostic for SMB outbound tech buyers: reduce manual research, improve decision-maker contact data, and tighten qualification and routing. It provides a clear structure for a comparison guide or assessment offer.
Shows the system behind the volume and connect-rate claims: proprietary data, targeting algorithms, outbound software, and recruiting.
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Start here for the operating model rather than a single tactic.
Describes DataLane Deployed as a bet that a better sales system can make BDRs 5–6x more productive than average.
One Deployed rep booked 17 demos for a customer in a week while every rep averaged over 200 dials daily.
The system combines an SMB Data Graph with 20M+ accounts refreshed weekly and signals such as pre-business openings; AI targeting algorithms called Next Best Dial and DM Boost, trained on millions of dispositioned dials and iterated weekly; Flow, outbound software built specifically for SMB selling; and premium BDR managers, BDRs, and sales enablement hires.
For brands planning a campaign
This system-level pitch gives a sales technology company a model to position against or learn from: data coverage refreshed weekly, proprietary dial-prioritization models, purpose-built outbound software, and talent density. It supports campaign messaging around integrated systems rather than standalone lead lists.
Explains a concrete targeting idea: not just who to call, but when to call each type of local business.
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Start here for the data-driven targeting side of the SMB outbound strategy.
Introduces Next Best Dial, an algorithm being built to prioritize accounts by predicted decision-maker connect rates on a given day.
Patterson-Cole says a key component is finding the best time to dial by vertical and business type, with different optimal windows for places like a bar, a bakery, and a restaurant open for lunch.
They say it also factors in the number of dial attempts, pickup history, and role.
The goal is for the machine to serve the best account and contact in the moment, so the SDR can focus on selling rather than manually processing data.
For brands planning a campaign
A campaign can promote time-of-day and business-type sequencing as a practical targeting differentiator. The post makes the abstract algorithm concrete with a specific example: bar versus bakery versus lunch restaurant.
Sets a target that turns the volume thesis into a daily operating metric.
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Start here for the connect-rate benchmark and why Patterson-Cole sees outbound as a competitive advantage.
Says sales reps need 15 or more decision-maker connects per day for SMB outbound to work, with 30 or more described as the new gold standard, while most outbound teams are at 5–7.
Patterson-Cole says this is hard, and that inbound remains a strong channel but is getting more expensive and does not drive enough volume for many companies.
The post frames effective outbound as rare and therefore a major competitive advantage: BDRs who generate predictably more conversations and revenue let a company reinvest in product, brand, and performance marketing.
It also references a CRO named Kyle and the DataLane Deployed offering.
For brands planning a campaign
Use the 15+ connects benchmark as a campaign hook for a connect-rate or dial-volume offer. It supports positioning outbound as a way to build a compounding advantage, not just a lead source.
For outbound to small businesses, Patterson-Cole argues the first lever is usually more dials, not better targeting or conversion work.
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Most teams put roughly 90% of their effort into conversion and signals, yet conversion is hard to move: even a 50% lift rarely shifts closed-won revenue much on its own.
Cold-call volume is easier to change.
The average SMB rep dials about 50 times a day, and Patterson-Cole says that can be doubled within a week.
Reps they have trained have peaked above 300 dials in a day.
Patterson-Cole compares volume and conversion as competing levers, then models the revenue impact of raising dial counts.
For brands planning a campaign
A sales technology brand can build content or demos around raising daily dial volume — dialer throughput, list preparation, coaching targets — instead of framing signals as the primary fix.
Patterson-Cole reduces cold-call-heavy SMB outbound to Volume x Connect Rate x Conversion, then identifies the common failure in each part.
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Volume: reps do not dial enough, and manual account research eats into selling time — they say every minute of manual research between accounts adds more than an hour of non-selling time per day.
Connect rate: reps spend too little time with decision makers, so better mobile numbers and call timing make a large difference.
Conversion: reps talk to accounts that will never close, so teams need more disqualification, fit scoring, and routing to the right rep.
Patterson-Cole's answer is to stack wins across all three rather than search for a single fix.
A component-by-component diagnosis of why SMB outbound programs lose money, citing a best-in-class example of an organization adding more than $1m ARR per rep.
For brands planning a campaign
A campaign can use this three-part structure, treating dial volume, decision-maker contact data, and qualification or routing as separate content tracks or offers rather than promising a single fix.
Patterson-Cole treats decision-maker connects on cold calls as the most important variable in SMB outbound.
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In their framing, reps need at least 15 decision-maker connects a day for outbound to work, with 30 or more as the new gold standard; most teams sit at 5 to 7. They say the target is hard to hit and effective outbound is rare, making it a durable advantage: teams that reliably generate several times more conversations and revenue can reinvest in product, brand, and performance marketing, while competitors are pushed into a slower, cash-flow-positive game.
For brands planning a campaign
A brand selling to SMB sales teams can anchor its messaging on a daily decision-maker connect target and offer tools or training to make the number visible and improvable.
Patterson-Cole describes Next Best Dial, an algorithm they are building with Emile Flavin and Matthew Danics to rank accounts by predicted decision-maker connect rate for that day.
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A key input is the best time of day to dial by vertical and business type — the optimal window for a bar, a bakery, or a restaurant open for lunch differs — alongside number of dial attempts, pickup history, and role. The aim is for software to surface the best account and contact at any moment so reps spend time selling rather than analyzing data.
A prediction model trained on dial dispositions and account data, iterated weekly.
Patterson-Cole describes testing and intent for Next Best Dial, but reports no measured lift. Ask for results before using the model's performance to guide a buying decision.
For brands planning a campaign
A targeting or sales-engagement product can build a campaign around time-of-day and business-type dialing windows, and tools that remove manual prioritization from the rep's day.
The data graph, AI targeting, and purpose-built software stack
Describing DataLane Deployed, Patterson-Cole lists four ingredients behind reps averaging over 200 dials a day and one rep booking 17 demos in a week: a proprietary SMB data graph, built with seven-figure annual investment and 20M+ SMB accounts refreshed weekly with signals such as pre-business openings; AI targeting algorithms, including Next Best Dial and DM Boost, trained on millions of dispositioned dials and iterated weekly; Flow, outbound software rebuilt for SMB selling that half of the engineering team worked on; and premium hires across BDR management, reps, and sales enablement.
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They frame the goal as making BDRs 5-6x more productive than average.
For brands planning a campaign
A sales-tech brand can use this four-part stack as a content framework, but should make clear that the data, algorithms, and software are Patterson-Cole's own product build, not neutral buying advice.
David Patterson-Cole's work begins with a claim about SMB outbound: teams chase conversion and signals when more daily calls and more decision-maker conversations are easier levers to move.
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The three-part diagnostic—volume, connect rate, conversion—shows how the pieces fit together, followed by posts on call timing, account data and purpose-built outbound software.
For the practical layer, read the posts describing Next Best Dial and the DataLane Deployed stack.
The performance figures are the author's own claims about a system being built; ask for independent test results before relying on them.
Together, the posts make one operating argument: raise activity first, then make it smarter with data, timing, qualification and software.
Lingenfelter writes about rebuilding SMB and mid-market outbound from the ground up, treating pipeline as a system rather than a single tactic.
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One post describes a manufacturer that went from 10 to 12 opportunities a year to 23 sales qualified appointments a month by rebuilding targeting, activation and conversion; it names conversion as the piece most teams skip. The structure—enough top of funnel, plus something built to catch it—echoes Patterson-Cole's view that volume alone isn't the answer and each part of the motion needs attention.
Lingenfelter's argument focuses on full-funnel design and agency craft: a component-by-component rebuild of targeting, activation and conversion, alongside a post about the competitive drive behind building a sales development agency. Their posts don't address call-volume benchmarks, decision-maker connect targets, or proprietary data and algorithm work—the core of Patterson-Cole's material.
Sundar writes about sales development and revenue operations systems, including how Rippling scaled from a 30 to 40 person outbound team to a 400+ BDR organisation by defining the SDR-to-AE handoff and adding an AI workflow to check call recordings against rules of engagement.
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Both writers treat outbound as a motion to be deliberately designed, with AI as a layer in that design rather than a replacement for it.
Sundar focuses on revenue operations inside a scaling company: handoff definitions, qualification stages, win-loss feedback loops and continuous revenue intelligence.
They name tool categories such as competitive intelligence and call recording platforms.
Patterson-Cole focuses more closely on the dial itself: daily call counts, decision-maker connect rates, best time of day to call, and account data built for local SMB selling.
Marin also applies data and AI to outbound prospecting.
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One post argues that a company's best existing customers are the blueprint for the next hundred deals.
It describes extracting firmographic data, buyer roles and the language that converted them, then feeding that information into lead research and copywriting agents.
The view that targeting should be built from evidence rather than generic best practices is shared ground with Patterson-Cole's account-based, data-graph-first approach.
Marin argues that well-designed automation can produce higher-quality outreach than most human BDRs by removing fatigue and inconsistency, and describes fully automated end-to-end campaigns. Patterson-Cole makes the opposite wager: build the best sales system to make human BDRs several times more productive, leaving the call with a person while the machine decides which account to call and when.
Placement decision: the available figures support a modest LinkedIn following for SMB outbound sales content, but do not verify the audience’s roles or seniority.
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David Patterson-Cole’s LinkedIn profile shows 3,499 followers as of October 8, 2026.
Five posts published between August 26 and October 5, 2026, address SMB outbound sales operators and leaders, covering cold-call volume, decision-maker connects, targeting algorithms, and sales-system building.
The posts do not report audience geography, age, gender, employer, occupation, or job seniority, and no audience survey data is published.
For a sales-technology campaign, ask Patterson-Cole for recent audience survey results or platform demographics covering job role, seniority, industry, and geography, plus recent performance for comparable SMB outbound topics and formats.
That information would help determine whether the audience fits the campaign rather than relying on follower count alone.
David Patterson-Cole’s posts focus on sales methods and products, including cold-call volume benchmarks, decision-maker connect-rate targets, the Next Best Dial targeting algorithm, and the DataLane Deployed service.
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They do not disclose sponsorship packages, rates, or a media-kit inquiry route.
Named people and companies appear as colleagues, customers, or peers—not as disclosed paid placements: Emile Flavin and Matthew Danics are credited with building the Next Best Dial algorithm, a CRO named Kyle is described as a thought partner in rolling out DataLane Deployed, and Owner is cited as a best-in-class example of outbound economics.
Buyers should contact Patterson-Cole directly to discuss a paid collaboration.
A B2B sales technology company selling a dialer, sales-engagement tool, or SMB contact-data product wants a practitioner-led campaign on making SMB outbound profitable.
Reasons
Patterson-Cole’s content maps directly to the buyer’s problem: SMB outbound economics, cold-call volume, decision-maker connect rates, and data-driven call targeting.
The posts offer concrete operating numbers for a campaign: an average SMB rep dials about 50 times a day; teams can reliably double that within a week; trained reps peaked above 300 dials a day; and reps need 15 or more decision-maker connects a day, with 30 or more described as the new gold standard.
The three-part frame—volume × connect rate × conversion—gives sales-technology buyers a simple structure for content, assessments, or a pilot offer.
Examples of optimal calling windows for a bar, a bakery, or a lunch restaurant make a targeting product tangible for SMB sales teams.
The posts don’t show a published sponsorship package. Ask about collaboration terms and pricing.
Risks
The content is closely tied to DataLane Deployed, the SMB Data Graph, Next Best Dial, DM Boost, and Flow. A direct competitor to that system may find the association awkward or conflicting.
As of 8 October 2026, the LinkedIn account had 3,499 followers. The posts don’t provide audience demographics by role, seniority, industry, or geography; ask for those details and reach data.
The posts describe testing, intent, and internal examples, but report no measured lift for Next Best Dial.
When to choose a specialist
Poor fit.
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Brief
A consumer brand, lifestyle publisher, or broad-reach B2B brand wants large audience scale, trend or entertainment content, or an off-the-shelf sponsored post package with published rates and demographic guarantees.
Reasons
The five posts on LinkedIn focus on SMB outbound sales, not consumer, lifestyle, entertainment, or broad-category content.
As of 8 October 2026, the LinkedIn account had 3,499 followers—not a large multi-platform audience. The posts don’t provide audience demographics; ask for role, seniority, industry, and geography.
The posts show no sponsorship packages, rate terms, media-kit inquiry route, or disclosed paid-collaboration examples. Ask for the offer and terms before planning a campaign.
The posts promote Patterson-Cole’s own sales system and operating model. A brand seeking neutral third-party buying advice or independent product comparisons won’t find it here.
The posts report no measured results for comparable sponsored content. Ask for performance data before committing to a campaign.
A worked campaign example
Brief
A sales-engagement platform wants to win SMB outbound teams away from signal-led tools by showing that volume-first execution is the faster path to more conversations.
Campaign angle
The 15-connect day: diagnose volume × connect rate × conversion before buying more signals.
Content sequence
Lead piece: the outbound formula—volume × connect rate × conversion—and the common failure in each part. Include the claims that average SMB reps dial about 50 times a day, volume can reliably double within a week, and manual research between accounts can add more than an hour of non-selling time per day.
Practical tool: a simple volume calculator or worksheet modeling how closed-won revenue changes as daily dials rise, using the post’s point that a conversion lift barely moves revenue without a matching volume increase.
Second piece: the 15+ decision-maker connects benchmark, with 30+ described as the new gold standard and most teams at 5–7. Frame effective outbound as a competitive advantage that lets a company reinvest in product, brand, and performance marketing.
Third piece: time-of-day targeting by business type, using the bar, bakery, and lunch-restaurant examples. Show how software can surface the next best account and contact so reps spend time selling rather than analyzing data.
Closing offer: an SMB outbound volume assessment to measure daily dials, decision-maker connects, and conversion, then choose one operating change for the next two weeks.
Call to action: request a baseline dial-and-connect audit, not a generic demo.
Measurement
Track qualified SMB outbound leaders who complete the volume diagnostic, request the worksheet, or book a baseline audit. Don’t judge the campaign on follower count alone.
Proof points to use
Volume beats conversion for SMB cold calling: the average rep makes about 50 dials a day; teams can double that within a week; trained reps peaked above 300 dials a day.
Decision-maker connects: 15+ per day needed, 30+ described as the new gold standard, most teams at 5–7.
The three-part diagnostic: volume × connect rate × conversion. Specific failure points include insufficient dialing, too little decision-maker talk time, and conversations with accounts that will never close.
Next Best Dial predicts decision-maker connect rates by time of day and business type, with different windows for a bar, a bakery, and a lunch restaurant.
DataLane Deployed claims 200+ dials per rep per day, one rep booking 17 demos in a week, an SMB Data Graph with 20M+ accounts refreshed weekly, and AI targeting algorithms iterated weekly.
What to ask before buying
Recent audience demographics by job role, seniority, industry, and geography.
Recent performance for comparable SMB outbound topics and formats.
Any paid-collaboration terms, sponsorship policy, or conflict rules involving competing sales-engagement or data products.
Ask whether measured results exist for Next Best Dial or comparable outbound campaigns beyond the internal examples in the posts.
Confirm how DataLane Deployed, Flow, and the SMB Data Graph would be represented in the campaign, so the sponsor's product is not confused with its brand.
Why it works
Their strongest argument: most teams overspend attention on conversion and signals, while cold-call volume is easier to move. The campaign can turn that into a practical diagnostic rather than a generic thought-leadership post.
Choose Lingenfelter for a campaign aimed at building the conversion layer behind outbound rather than raising dial volume.
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One post describes a manufacturing quality software company generating 10 to 12 new opportunities a year that was rebuilt across targeting, activation, and conversion to reach 23 sales qualified appointments a month, 78 booked appointments in a quarter, and 5 closed-won deals.
The argument that deep tech, AI, and human SDRs only work when wired together as one system suits a buyer selling outbound enablement, sales-development services, or a full-funnel system.
Posts on agency life and competitive drive also fit operator- or culture-led content for a BDR-services audience.
The material offers one detailed case and one competitive-mindset post, but no dial counts, decision-maker connect benchmarks, or time-of-day targeting rules.
A buyer selling a dialer, contact-data tool, or call-targeting algorithm has less here to build a measurable, volume-first campaign around than Patterson-Cole's volume x connect rate x conversion diagnostic.
The manufacturer example covers a single account, so ask for evidence that the approach is repeatable.
Choose Sundar for a campaign focused on enterprise BDR scaling, SDR-to-AE handoff design, or continuous win-loss and competitive intelligence.
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They describe Rippling rebuilding sales development from 30-40 outbound BDRs to a 400+ BDR organisation, with Stage 1 qualification on authority, need, and timeline; an AI workflow checking Gong recordings against rules of engagement before an opportunity advances; and new SDRs trained inbound-first as a route into AE and leadership roles.
They also use Jevons Paradox to argue AI expands RevOps demand rather than shrinking it, and describe win-loss shifting from a quarterly exercise to a live feedback loop, citing Klue, Crayon, Hyperbound, Gong, Highspot, and Avoma.
That fits a buyer selling RevOps, conversation-intelligence, or sales-enablement software into larger organisations.
These are large-company processes measured in qualification stages and handoff rules, not SMB cold-call economics.
Sundar's posts give no daily dial volumes, connect-rate targets, or business-type call timing.
A campaign promising dialing volume or SMB data-driven targeting would need that evidence from elsewhere.
Tool mentions are references rather than demonstrated integrations, and the Rippling figures describe one company's reorganisation.
Choose Marin when the buyer sells outbound automation, lead-data, or AI agent tooling and wants an automation-first position.
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The material argues that fully automated outbound campaigns can handle data enrichment with precise targeting, context-aware personalisation at scale, multi-channel coordination, real-time response handling, and performance optimisation.
It claims well-designed automation can produce higher-quality outreach than most human BDRs by removing fatigue, inconsistency, and knowledge gaps.
A companion post explains turning top-LTV customers into a targeting and copywriting blueprint using a directory of 70m+ accounts.
That suits a vendor whose product replaces or reduces manual rep work.
Marin's automation-first framing contrasts with Patterson-Cole's claim that cold-call volume, not signals, moves SMB revenue, and offers no dial counts, connect-rate benchmarks, or call-timing data. A buyer selling a dialer or human-SDR service may not want the featured argument to be that automation outperforms human reps.
David Patterson-Cole's five LinkedIn posts here are about selling to small and midsize businesses.
They cover the argument for raising call volume before chasing better conversion, a diagnostic that splits outbound into volume, decision-maker connect rate and conversion, daily decision-maker connect benchmarks, a model for choosing which account to call and when, and a description of a combined account data, algorithm and software system.
No interviews, podcast or video transcripts, third-party coverage, audience data or sponsorship documents are discussed here.
The posts have no publication dates, so the order in which these arguments developed cannot be established.
LinkedIn showed 3,499 followers on 8 October 2026, with no breakdown by role, seniority, industry or geography.
The posts describe performance figures as the author's own claims about an internal system being built, not as independently tested results.
This profile does not verify employers, credentials or outcomes.
