A data-driven analysis of B2B sales connection rates in 2024, comparing mobile numbers, direct office lines, and HQ switchboards based on industry reports.

In 2024, mobile numbers delivered the highest connection rates for B2B sales outreach, significantly outperforming traditional phone types. While specific unified reports are fragmented, synthesis of available data indicates mobile numbers connect 45-60% more often than office lines. [9, 13] The average cold call success rate was 4.82% in 2024, a benchmark that top teams exceeded by leveraging verified mobile and direct-dial data to bypass gatekeepers and low-performing switchboard numbers. [1, 5] This performance gap underscores the critical role of data quality in modern go-to-market strategies.

TL;DR

The average B2B cold call success rate jumped to 4.82% in 2024, making phone outreach a high-value channel. [1]
Mobile numbers have a 45-61% higher connection rate than office or direct lines, according to analyses from Nooks and Martal Group. [9, 13]
Using a direct dial instead of a switchboard makes a sales rep 147% more likely to connect with a VP-level prospect, per ZoomInfo research. [5]
Data from Cognism shows top-performing teams achieve success rates over 11% by using verified mobile data, more than 4x the industry average. [3, 4]
Poor data quality costs organizations millions, with B2B contact data decaying at a rate of 22.5% annually. [7]

2024 Connection Rates: Mobile vs. Direct vs. HQ Numbers

Synthesizing available 2024 and 2025 data reveals a stark performance hierarchy among phone number types, even without a single, universally accepted benchmark report. Analysis from multiple data providers indicates that teams using verified mobile and direct-dial numbers operate on a completely different performance tier than those relying on traditional headquarters lines. According to 2024 benchmark data from Gong, the average B2B cold call connect rate hovers between 7% and 9%. However, this figure is a blended average that masks the inefficiency of switchboards; reports from data providers like Lusha show that verified direct dials connect at a much higher rate of 12% to 18%, while general company lines fall to a meager 2% to 4%. Cognism's 2025 State of Cold Calling Report further refines this, showing that SDRs using their phone-verified data achieved a 13.3% answered rate on cold outreach, a figure nearly identical to the 14.4% rate for account executives calling warm leads. This data collectively suggests an estimated connection rate of 9-12% for high-quality mobile numbers, 6-8% for standard direct dials, and a rate consistently below 3% for switchboards, establishing a clear case for prioritizing data quality in any modern outbound strategy.

The significant performance lift from mobile and direct-dial numbers is not just a marginal gain but a fundamental advantage in reaching prospects. An analysis by the dialing platform Nooks.ai, based on data from over three million calls, found that mobile numbers have a 45% higher connect rate than non-mobile work lines. This finding underscores a critical shift in a hybrid-work environment where desk phones are often left unanswered. The advantage extends beyond simply getting an answer; it directly impacts the ability to reach senior leadership. Research attributed to ZoomInfo highlights this by showing that using a direct dial instead of a switchboard number increases the likelihood of connecting with a director by 46% and with a vice president by a remarkable 147%. This capability to bypass gatekeepers and connect directly with budget-holders transforms data from a simple contact list into a strategic tool for accelerating sales cycles and improving the quality of sales conversations. For sales teams, this means the difference between a call that ends with a receptionist and one that starts a qualified opportunity.

Beyond connection probability, the efficiency gains from using direct-dial numbers translate into substantial productivity improvements and reduced operational waste. The time cost of navigating a corporate switchboard is a significant drain on sales resources. Multiple industry analyses, including research from SalesIntel's 2026 report, confirm that it takes an average of 22 minutes to successfully connect with a prospect when starting from a main company number, compared to just five minutes when using a direct dial. This four-fold difference in time-to-connect means that a sales representative could make more than four direct-dial connections in the time it takes to achieve one through a switchboard. For a team of sales development representatives, this lost time accumulates into hundreds of hours of unproductive activity each month. This stark contrast in efficiency makes a compelling argument for investing in premium data solutions that provide verified, human-vetted direct numbers, as the return on investment is realized through dramatically increased talk time and more meetings booked per representative.

Data Provider / Source	Metric	Reported Value	Phone Type	Report / Year
Gong (via Lusha)	Average B2B Connect Rate	7-9%	All (Blended)	2024
Lusha	Connect Rate Benchmark	12-18%	Verified Direct Dial	2026
Saleshive / Lusha	Connect Rate	2-4%	Switchboard / General Line	2026
Nooks.ai	Performance Lift vs. Non-Mobile	45% Higher Connect Rate	Mobile	2023 (from 3M+ calls)
Cognism	SDR Answer Rate (Cold Outreach)	13.3%	Verified Contact Data	State of Outbound 2026
ZoomInfo (via Outsales.ai)	VP Connect Likelihood Increase	+147%	Direct Dial vs. Switchboard	2026
SalesIntel	Average Time to Connect	5 minutes vs. 22 minutes	Direct Dial vs. Switchboard	2026

The Data Quality Mandate: Why Verified Numbers Matter

B2B contact data decays at a relentless pace, with industry benchmarks indicating an annual decay rate of 22.5%, effectively making a quarter of a sales team's database obsolete within just twelve months. [4, 6] Research published by Cleanlist in February 2026 confirms this figure, which is driven by predictable events like job changes, corporate acquisitions, and phone number updates. [4] In high-turnover sectors such as technology, this degradation can accelerate to as much as 70% annually. [4] The root cause is largely workforce mobility; Bureau of Labor Statistics data from January 2024 reported the median employee tenure fell to 3.9 years, implying a significant portion of any contact list becomes invalid each year from job changes alone. [8] This constant state of decay means that without a continuous verification strategy, sales teams are systematically funneled toward disconnected numbers and bounced emails, which not only wastes resources but also actively damages sender reputation and reduces the deliverability of all future outreach efforts. The compounding nature of this decay, estimated at 2.1% per month, turns static CRM data into a significant liability. [4, 8]

The operational cost of this data decay materializes as a severe drain on sales productivity, with multiple analyses concluding that representatives waste approximately 27% of their time contending with inaccurate contact information. [7, 9] According to research from Landbase updated in April 2026, this inefficiency translates to 550 lost hours and a productivity cost of $32,000 per representative each year. [7] For a mid-sized sales team, these hours represent a substantial hidden expense, diverting focus from revenue-generating activities like prospecting and closing deals to administrative dead ends like correcting records and troubleshooting bounced outreach. The broader financial impact is even more stark. A 2026 Gartner study frequently cited by firms like Salesmotion and Datamatics estimates that poor data quality costs the average organization $12.9 million annually through a combination of wasted marketing spend, operational drag, and missed sales opportunities. [6, 11] This is not a passive background issue; it is an active drain on pipeline velocity and a primary driver of inefficiency that prevents teams from performing at their full potential.

Implementing a rigorous data verification mandate is the most direct way to reclaim lost productivity and gain a significant performance edge in a competitive market. While specific lift varies, validated phone numbers drastically increase the probability of connecting with the right decision-maker on the first attempt, allowing sales teams to bypass the productivity sinks of wrong numbers and outdated information. [27] The downstream impact is substantial, as research highlighted by Landbase in a January 2026 report shows companies using accurate contact data achieve 66% higher conversion rates compared to those working from unverified lists. [28] This performance improvement stems from reallocating representative time from data janitor work to high-value conversations. Investing in high-quality, verified data from a provider like SalesIntel, which offers human-verified contacts, ensures that outreach efforts are consistently directed at actionable leads, speeding up the sales cycle and boosting team morale by ensuring their efforts yield tangible results. [17, 21] Ultimately, accurate data is not just a defensive measure against decay; it is a strategic asset that directly fuels higher connection rates and revenue growth.

Cost vs. ROI: Is Premium Mobile Data Worth the Investment?

The investment in premium mobile data is justified by the significant, yet often hidden, costs associated with low-quality contact information. B2B contact data pricing exhibits a wide variance, with reported costs ranging from under $0.10 to over $1.50 per contact, contingent on the provider and the depth of verification. However, this initial price tag obscures the true cost of ownership. A cheaper contact that bounces or is outdated is fundamentally more expensive than a pricier, verified contact that leads to a connection. Research indicates that poor data quality can cost organizations an average of $12.9 to $15 million annually through wasted spend, lost productivity, and missed revenue opportunities. Sales representatives can lose up to 550 hours per year, equivalent to $32,000 in lost productivity per rep, simply dealing with the fallout of bad data. This lost time includes researching correct information, managing bounced emails, and dialing disconnected numbers, all of which could be reallocated to active selling. The principle known as the 1-10-100 rule illustrates this escalating cost: it costs $1 to prevent a bad record, $10 to cleanse it later, and $100 to deal with the consequences of not fixing it at all. This framework highlights that prioritizing data accuracy from the outset is the most financially sound strategy.

B2B data platforms create a clear value hierarchy for different data types, with verified mobile numbers positioned as a premium asset commanding the highest price. On a platform like Apollo.io, for instance, revealing a mobile number can cost 8 credits, whereas a basic email reveal costs only 1 credit, establishing an 8:1 value ratio. This credit-based pricing model, common among vendors like Lusha as well, forces sales leaders to make strategic decisions about where to allocate their data budget. Some providers, such as SalesIntel, differentiate themselves by including human-verified or machine-verified mobile numbers as a standard feature in their offerings, contrasting with competitors who often treat it as a premium, credit-intensive add-on. Other enterprise-focused vendors like Cognism build their entire premium tier, such as its "Diamond Data" offering, around providing phone-verified mobile numbers, with entry-level contracts starting around $20,000 per year. This pricing structure underscores that while all data has a cost, the market places a significant premium on the data points, like mobile numbers, that provide the most direct and effective path to decision-makers, bypassing traditional gatekeepers.

Calculating the return on investment for premium mobile data requires looking beyond the per-contact cost and focusing on the total impact on sales productivity and efficiency. The ROI formula for data quality initiatives measures the financial benefits against the investment, encompassing factors like increased revenue and reduced operational costs. A critical metric to consider is the cost of wasted effort; sales reps waste an estimated 27% of their time on bad data, a significant productivity drain that directly impacts revenue generation. Consider a scenario where a sales team uses lower-quality, cheaper data with a high bounce and no-connect rate. The time spent verifying information and dealing with invalid contacts represents a substantial opportunity cost. In contrast, investing in a higher-cost, verified mobile number dataset that increases connection rates by even 30-40% can dramatically alter this equation. The incremental cost of the premium data is often dwarfed by the value of the additional conversations and meetings it generates, transforming sales rep downtime into active selling time and accelerating the entire sales cycle. As research from Gartner suggests, poor data quality can cost businesses up to 15% of their revenue, making the upfront investment in accuracy a powerful lever for maximizing overall financial performance.

Vendor	Mobile Data Model	Estimated Cost per Mobile Number (2026)	Verification Method	Key Differentiator
Apollo.io	Credit-based (8 credits/number)	~$0.16 - $0.21	Automated data collection and verification.	All-in-one sales platform with a large contact database at a low per-seat cost.
Lusha	Credit-based (5-10 credits/number)	~$0.44 - $0.88	Community-sourced data with internal verification.	User-friendly Chrome extension and a free tier for individual users.
Cognism	Included in "Elevate"/"Diamond" Tier	High (part of ~$20k+ annual contract)	Phone-verified "Diamond Data" with human confirmation.	Premium, GDPR-compliant data with a focus on phone-verified mobile numbers for European markets.
ZoomInfo	Included in subscription (exports may be limited)	High (part of ~$15k+ annual contract)	AI/ML models, web crawling, human research, and NeverBounce for email verification.	Deep enterprise-grade database with extensive firmographic, technographic, and intent data.
SalesIntel	Included as a core feature	Varies (part of subscription)	Human-verified data, with researchers calling to confirm numbers.	Focus on 95% human-verified data accuracy, including work mobile and direct-dial numbers, with a research-on-demand service.
Lead411	Included in subscription (unlimited on top tier)	Varies (part of subscription, starts ~$99/mo)	Internal verification processes, includes sales trigger events.	Offers an unlimited export model on its Enterprise plan, which is rare in the market.

The SMB Data Gap: Why Local Businesses Are Harder to Reach

Major B2B data providers began a pronounced strategic shift away from small and medium-sized business customers in 2024, creating significant downstream consequences for sales teams. Citing higher churn and delinquent payments, incumbents like ZoomInfo actively started moving upmarket toward enterprise clients. A June 2026 report from S&P Global Ratings confirmed this pivot began around the second quarter of 2024, catalyzed by greater-than-anticipated customer write-offs from the downmarket segment, which it defines as organizations with fewer than 100 employees. [21] The report noted that this customer subset exhibited weaker net revenue retention, estimated at around 60% versus nearly 100% for upmarket clients, making the economic case for deprioritization clear. [21] This business decision, while logical for the provider, directly impacts the data available to the broader market. As market leaders reallocate resources to serve large enterprises, the data quality and coverage for smaller, local businesses structurally degrades, leaving a void for go-to-market teams that rely on this information to build pipeline and connect with prospects in the SMB space.

The strategic withdrawal of major players from the SMB market creates a significant data availability gap, making local businesses much harder for sales teams to reach effectively. This problem is compounded by the inherent difficulties of maintaining accurate B2B data, which decays rapidly as contacts change roles and companies evolve. This natural data decay can cost an enterprise millions per year, a problem that is particularly acute in the fragmented and dynamic SMB sector. [25] When a primary data aggregator shifts focus, the investment in refreshing and verifying information for downmarket accounts diminishes, leading to outdated contact information, incorrect firmographics, and an over-reliance on low-performing switchboard numbers. For sales teams targeting local plumbers, salons, or agencies, this translates directly to lower connection rates and wasted productivity. The challenge is not just a lack of data, but a lack of verified data, as platforms that once served this segment turn their attention to the more lucrative, and data-rich, enterprise landscape, a move detailed in a March 2025 conference presentation. [6]

Alternative data sourcing methods have emerged to fill the SMB data void left by incumbents, representing a distinct and high-value asset class. While enterprise data has become a commodity, verified data for local businesses is sourced through different, more meticulous means. Specialized providers address this gap by programmatically collecting information from public business directories, maps, and professional networks, then adding a critical layer of human verification to ensure accuracy. [10, 23] This methodology allows for the creation of high-fidelity datasets focused on business owners and key decision-makers at a local level, a segment that large-scale, automated platforms structurally struggle to resolve. According to SalesIntel, sales representatives using human-verified data are significantly more likely to connect with decision-makers, which boosts productivity and shortens the sales cycle. [23] This approach transforms public listings into a unique, high-value dataset that provides a competitive advantage, enabling sales teams to bypass the gatekeepers and low-quality information that now characterize the downmarket data provided by traditional vendors.

How Phone Data Impacts Modern Sales Cadences

Modern sales cadences are increasingly defined by efficiency, with data from 2026 showing a significant drop in the average dials needed to reach a prospect to just 1.55. This marks a substantial improvement from previous benchmarks, which often cited higher numbers, indicating a shift towards more precise targeting enabled by higher quality data. According to a 2026 report from Martal.ca, which references Cognism's State of Cold Calling data, this lower dial-to-connect ratio suggests that when sales development representatives (SDRs) have access to verified mobile numbers and direct-dial information, they spend less time navigating switchboards and more time in conversations. This efficiency is critical, as it directly impacts a team's overall productivity and ability to generate pipeline. The underlying driver for this trend is the adoption of advanced go-to-market intelligence platforms that provide cleaner, more accurate contact information, allowing sales teams to bypass gatekeepers and connect directly with decision-makers with unprecedented speed. This data-driven approach transforms the initial stages of the sales process from a high-volume, low-success guessing game into a targeted and effective outreach strategy, fundamentally changing the economics of cold calling.

Despite the gains in efficiency from better data, a persistent challenge remains: the number of attempts required to secure a connection. While it may only take 1.55 dials on average to reach a prospect who answers, not every prospect answers on the first try. Multiple data points suggest it takes an average of eight call attempts to finally reach a prospect, a figure that highlights a significant disconnect between best practices and common rep behavior. Research from TOPO, now part of Gartner, showed the median attempts needed climbed to 9.1 in Q1 2026, citing increased use of call screening and gatekeepers. The core issue is that a large percentage of sales representatives abandon the effort prematurely. For instance, one widely cited statistic indicates that 44% of reps give up after a single follow-up attempt, and the average rep makes only 1.7 to 2.1 attempts before moving on. This premature surrender leaves a substantial amount of potential pipeline untapped. The small fraction of reps who persist beyond four or five attempts are the ones who disproportionately capture deals, underscoring that data quality alone is insufficient without disciplined execution of the sales cadence.

Successful outreach is rarely a single-channel endeavor; top-performing sales teams embed their calling efforts within a broader, multi-channel cadence. The most effective of these sequences involve 8 to 12 touches, strategically interleaved across phone, email, and social media platforms like LinkedIn over a period of two to three weeks. This structure acknowledges the reality of modern B2B buying, where prospects engage with information across various platforms at their own pace. A 2026 analysis by Callbox Inc. noted that teams running these integrated multi-channel cadences can see reply rates up to 287% higher than those relying on email alone, a figure attributed to Cognism. This approach moves beyond isolated cold calls, creating a persistent and cohesive narrative around the value proposition. By combining channels, sales teams can cater to different communication preferences and increase the probability of engaging a prospect at the right time on the right platform, transforming sporadic follow-ups into a predictable system for generating engagement and booking meetings.

The effectiveness of a sales cadence is not just about the number of touches but also their timing. A consensus has emerged from multiple data analyses that the best days for B2B sales calls are midweek, specifically Wednesday and Thursday. A Salesmate study involving 12,480 call attempts found Wednesday to be the single best day, yielding 53.67% more successful conversations than Friday, the worst day. The optimal times to call are consistently identified as two distinct windows: mid-morning, between 10:00 AM and 11:00 AM, and late afternoon, between 4:00 PM and 5:00 PM in the prospect's local time. The late afternoon slot is particularly potent, with one analysis from SalesHive's 2026 benchmarks suggesting calls made between 4:00 PM and 5:00 PM are 71% more successful than those made in the late morning. This timing is effective because prospects have typically cleared urgent morning tasks and are often winding down their day, making them more receptive to a brief, unscheduled conversation. Aligning call blocks with these proven windows can lift connect rates significantly without any other changes to the outreach process.

Frequently Asked Questions

What is a good connection rate for B2B cold calls?

A good connection rate for B2B cold calls is between 15% and 20%, which indicates strong execution and high-quality data. Baseline performance using generic or unverified data typically yields a much lower connection rate, often between 4% and 6%. [13] Teams that leverage verified mobile numbers can expect to see rates between 6% and 10%, demonstrating the significant impact of data quality on reaching a live person. [13] Achieving a rate above 20% is considered highly optimized and is usually the result of a sophisticated system combining premium data, precise targeting, and consistent execution. [13]

Is it better to call a prospect's mobile or direct dial number?

It is significantly better to call a prospect's mobile number, as they connect far more reliably than traditional office lines. Research from 2024 shows that work mobile numbers can have a dial-to-connect ratio as low as 10:1, whereas direct desk dials are closer to 73:1, making mobiles over seven times more effective. [11] This performance gap is driven by the rise of hybrid work, as mobile numbers are tied to an individual rather than a physical office location. [11] Using verified mobile numbers is critical for bypassing gatekeepers and ensuring your call actually reaches the intended decision maker. [1]

How much more does verified mobile number data cost?

Verified mobile number data typically costs 5 to 10 times more than a verified email address from the same data provider. [14] While some vendors like ZoomInfo and Cognism require custom quotes for their premium data, other platforms operate on a credit system where a mobile number reveal consumes more credits than an email. [14, 15] For example, a provider might charge 1 credit for an email and 5 credits for a phone number, making the effective cost per mobile contact substantially higher. [14] This premium price reflects the higher value and difficulty in sourcing accurate, direct mobile numbers for B2B outreach. [10]

Why is it hard to find contact data for local businesses?

It is hard to find accurate contact data for local and small businesses primarily due to limited resources and a lack of centralized data management. [18] Unlike large corporations, small businesses often lack dedicated staff or expensive software to ensure their contact information is consistently updated and publicly available. [18, 19] This results in incomplete records, reliance on personal devices instead of official business lines, and data scattered across various platforms, making it difficult for B2B data providers to collect and verify. [16, 19] Consequently, sales teams face challenges like data entry errors, outdated information, and inconsistencies when trying to reach local business owners. [20]

What is the average success rate for cold calling in 2024?

The average success rate for B2B cold calling, defined as converting a conversation into a booked meeting, was 4.82% in 2024. [3] This figure represented a significant increase from the 2% average reported in 2023, highlighting a shift towards more data-driven and strategic outreach methods. [1, 3] However, this rate can vary significantly by industry, with some benchmarks placing the average closer to 2.3% when analyzing broader datasets. [4] Top-performing teams consistently outperform these averages by leveraging high-quality data and personalizing their approach to earn appointments. [5, 6]

Last updated: October 2026

Mobile vs. Direct Dial: 2024 Connection Rate Comparison