B2B Mobile Number Quality Score

Mobile numbers have become one of the most useful pieces of B2B contact data. People are able to connect more often, conversations start sooner, and there is less time spent getting passed around by front desk teams. The issue is that not every mobile number in your CRM is actually a good one. Some are old personal phones, some are mislabeled main lines, and many have not been checked in a long time. Because B2B phone data degrades quickly, teams need a straightforward way to tell which mobile numbers are actually ready to dial. This guide gives you a simple scoring system you can use on any list to spot the strong mobile numbers and filter out the ones that will no longer be useful.

TL;DR

• B2B contact data gets old fast. Studies put database decay at around 22% of contacts per year.

• Phone data is similar. Around 18% of phone numbers change every year.

• Cold calling benchmarks show connect rates in the 10 to 20% range, and many large studies put the average around 16.6% when the data is good.

• This article gives you a simple Mobile Number Quality Score from 0 to 100 so you can look at the mobile column in your CRM or CSV and quickly see which numbers are truly "dial-ready".

Who This B2B Mobile Phone Number Quality Score Is For

This guidance is for teams that already have mobile numbers in their CRM or spreadsheet, usually pulled from data providers, enrichment tools, or older lists. The challenge you are dealing with is not how to find mobile numbers, but figuring out which of the numbers you already have are actually worth dialing first. In short, you are trying to prioritize your existing list so your outreach starts with the highest value and most reliable contacts.

What a Dial-Ready B2B Mobile Number Means

For this article, a mobile number is considered dial-ready only if it is likely to be the correct person’s work-related mobile number instead of an old or unrelated personal number.

It also needs to have been checked or used recently enough to show that it still works, and when you call it, it should produce reasonable connect rates (for example reaching the right person at least once or twice after several calls) and clear confirmation that you are reaching the right person.

If a number falls short on any of these points, it can stay in your system, but it should not be treated as a top-tier mobile for outbound work.

The Mobile Number Quality Score

You can score each mobile number, or a sample from a list, based on three main pillars.:

1. Source and type

2. Freshness and verification

3. Real-world performance

Each pillar gets 0-33 points. After determining the scores of each of the three, use the following equation to get your Dial-Ready Score:

Dial-Ready Score = Source & type + Freshness & verification + Performance

You can apply this to each individual number, or you can average the scores across a list, a provider, or a segment.

Pillar 1: Source and Type

This pillar is about the source and type of number. Remember that this is the information you already have on the number in your own system, and not about how any provider collected it.

Good signs:

• You have a simple source tag, such as: inbound_form, sales_rep_update, customer_success_update or import_vendor_X_2025_10.

• You can see how the number entered your system, for example whether it came from a recent vendor file or an old CSV from years ago.

• The phone type is set to something clear like "work mobile".

Risky signs:

• The number shows up with no source tag at all, so you cannot tell if it came from a 2019 CSV or from last week.

• It’s in a generic phone column with no type, which means main lines, direct dials, and mobiles are all mixed together.

• It appears in several old imports with no dates or notes.

Scoring Sheet

Per mobile number:

0 - 10 points:

• No source info and no type, you only know that it exists in your system.

11- 22 points:

• A basic source tag such as the vendor or import, but the age varies and the type is sometimes missing.

23 - 33 points:

• A clear and recent source tag along with an explicit phone type set to "work mobile" or something similar, so you know exactly what it is.

Pillar 2: Freshness and Verification

Industry reports consistently show that B2B contact data decays at roughly 22% each year. Phone numbers in particular tend to change at a rate of about 18% annually for many businesses.

A mobile that was good 18 months ago has a good chance of being wrong today. Take a look at our article on the Hidden Cost of Bad Leads to get a better sense of what old data can cost you.

Good signs:

• You keep a last verified date on the mobile field

• There is at least one recent and successful dial logged, usually within the last 90 to 180 days

• Call notes show the number is still tied to the same person and company. For example a note saying that you spoke with them about a renewal last month.

Risky signs:

• There is no verification date at all.

• Several recent dials are marked "disconnected", "not in service", or "wrong person", and nobody has updated the field.

• The only clue you have is that the number came in through a bulk import more than a year ago.

Scoring Sheet

Per mobile:

0 - 10 points:

• Never verified or last verified more than 18 months ago.

11 - 22 points:

• Verified sometime in the last 6 to 18 months, or at least one successful call in that window.

23 - 33 points:

• Clear verification along with at least one successful dial within the last 90 to 180 days.

You don’t need perfect timestamps for every call. Even one or two simple fields such as a "last verified date" and a basic call outcome are enough to tell the difference between a number that was used recently and one that might not work anymore.

Pillar 3: Real-World Performance

In the end, a number either gets you to a real person or it does not. Large cold calling datasets show that connect rates, meaning the share of calls that reach a live person, usually fall somewhere between 10 and 20%. Recent studies narrow this even more, landing around a 16.6% average connect rate when teams are working with clean and well maintained data.

If your best mobile numbers only connect 2 to 3% of the time or mostly reach the wrong people, they are not really dial-ready.

Whenever you call the numbers, track the following:

Dial outcome

• Did the call connect to a human?

• Did the call disconnect or error out?

• Did the call endlessly ring or go to voicemail?

Correct person rate

• When it connects, is it the intended contact or someone else?

Downstream impact for segments

• How often do these calls lead to real conversations, meetings, or new opportunities compared with other types of numbers (like main line or desk numbers)?

After your call, add the following in your CRM or system:

• Connected: correct person.

• Connected: wrong person.

• Disconnected or errored out.

• Always goes to voicemail or never picks up.

Scoring Sheet

Per mobile number:

0 - 10 points

• Very low connect rate with frequent bad number or wrong contact outcomes.

11 - 22 points

• Mixed results with some good connects and some poor ones.

23 - 33 points

• Connect rates and correct person rates that match or outperform the 10 to 20% benchmarks above.

Putting the Score Together

Once you have the three pillar scores, add each of the scores to get your Dial-Ready Score:

Dial-Ready Score = Source & type + Freshness & verification + Performance

Then group the mobile numbers into buckets:

80 - 100 (dial-ready):

• The mobile number is fresh and clearly identified as a work mobile with a solid performance track record. This means the number is generally safe to prioritize in your outbound sequences and call blocks.

50 - 79 (usable but unproven):

• The mobile number is fine for manual dials and lower volume testing, but keep an eye on how it performs before placing it in heavy rotation.

Below 50 (low-confidence mobile):

• The mobile number should be kept for research or as a backup, and you should plan to update or replace it when you can.

How to Start Scoring in 4 Steps

Start checking the quality of the mobile numbers in 4 simple steps.

Step 1 - pick a sample:

Choose a set of 50 to 200 mobile numbers pulled from a recent campaign, from one data provider, or from an important segment such as your main ICP.

Step 2 - add three simple fields:

• mobile_source

• mobile_last_verified_at

• mobile_performance

Step 3 - score the sample:

For each mobile number in your sample, assign a Source & Type score from 0 to 33, a Freshness & Verification score from 0 to 33, and a Performance score from 0 to 33 based on call outcomes or rep feedback. Add them together and record the final Dial-Ready Score.

Step 4 - act on it:

Prioritize mobile numbers that score 80 or higher in your upcoming call blocks. Numbers between 50 and 79 are better suited for manual or lower volume outreach. Anything below 50 should usually be left out of aggressive dialer campaigns.

Once this small sample proves effective, you can start using the same scoring approach on a larger set of records. From there, you can build simple dashboards such as average mobile score by provider to get a quick view of overall data quality. This makes it much easier to decide which lists and sources you can trust most for mobile heavy outreach.

FAQ

Do I need to score every single mobile number in my CRM?

No. Start with a sample from a specific provider, campaign, or ICP segment. Even scoring 50 to 100 mobile numbers will reveal clear patterns in which sources and time periods are giving you the strongest dial-ready numbers.

What if I don’t have detailed call outcome data yet?

You can still score using the first two pillars, source & type and freshness & verification. As you start logging basic call outcomes, you can update the performance pillar and refine the scores over time.