What Is Dibz?

Dibz is a prospecting tool that helps me find link building opportunities fast. It pulls leads from the web using search footprints and prebuilt filters. I get spam signals and quality metrics in one clean dashboard. Therefore I can sort by niche and location and platform in a few clicks. Moreover I can save lists and tag prospects for outreach later.

Key things I use every week

• Smart prospect search with custom footprints 🔍
• Spam checks with quick risk signals 🚦
• Filters by TLD, platform type, language, location 🌍
• Bulk actions for list building and exports 📦
• Saved searches and tags for repeat tasks 🗂️
• Simple dashboard with role friendly toggles 🧭

How it works for me

• I start with a keyword set and a footprint
• Then I apply spam filters and quality ranges
• Next I review titles and snippets for fit
• After that I tag and export to my outreach app
• Finally I track outcomes and refine the query

Feature snapshot vs common needs

• Guest post prospecting: finds blogs with clear guidelines
• Resource page outreach: locates curated lists in my niche
• Unlinked mentions: spots pages that talk about my brand
• Local link hunts: filters by city or region
• Digital PR angles: pulls media pages and journalist bios

Performance and accuracy

• The SERP parsing feels quick on modest queries
• However very broad footprints can add noise
• The spam score helps me prune weak domains
• Additionally the export keeps my CSV tidy for mail merge

My sample session from this week

Quick bar chart of strengths

• Speed 🟩🟩🟩🟩⬜
• Relevance filtering 🟩🟩🟩🟩🟩
• Learning curve 🟩🟩🟩🟩⬜
• Export workflow 🟩🟩🟩🟩🟩
• Reporting depth 🟩🟩🟩⬜⬜

Design and usability

• The UI uses clear labels and big filters
• Moreover the results grid shows the data I need at a glance
• I like the quick toggle for social presence and contact hints
• Dark mode keeps long sessions easy on my eyes

How it compares

• Ahrefs excels at broad research and link indexes yet I still open Dibz when I need fast prospect lists
• Pitchbox handles outreach sequencing yet I prefer Dibz for upstream prospect gathering
• BuzzSumo shines for content trends yet Dibz gets me actionable link targets faster

Who will like it

• Solo SEOs who need quick wins
• Small teams who want a repeatable process
• Agencies that must produce clean lists for clients

Value and pricing take

• I pay for speed and focus here
• Also I avoid bloated suites that slow my day
• Therefore the tool pays off when I run weekly prospect sprints in 2025

Pro tips from my workflow

• Start narrow with tight footprints then expand only if needed
• Use tags for campaign themes like guest post fintech or resource sustainability
• Pause on sites with vague write for us pages since response rates drop
• Keep one master blacklist to avoid repeat spam traps

• Start a search on Dibz and build your first list today 👉 https://dibz.me/

Key Features

Dibz packs the prospecting muscle I reach for each week. Here is what truly helps my outreach move faster and smarter.

Link Prospecting And Discovery

I start with focused keyword sets and Dibz returns fresh prospects in minutes 🧲

• I tap outreach types like guest posts, resource pages, product reviews
• I switch by intent such as mentions, citations, PR lists
• I set niche, country, language and the results stay tight
• I preview titles and snippets so I spot fit at a glance
• I add winners to lists with a single click

Tip: I save a template for each campaign so I keep results consistent across weeks.

Advanced Search Operators And Queries

I write precise queries and Dibz backs me up with power operators 🔎

• I combine footprints like “write for us” OR “guest post” with my topic
• I exclude forums or coupon sites with minus terms
• I lock exact phrases with quotes and set site limits with site:
• I target title or URL with intitle: and inurl:
• I use wildcards to catch variants when a niche uses mixed phrasing

So I cast a smart net and skip hours of manual Google gymnastics.

Spam And Quality Metrics Integration

Quality control sits inside my prospecting flow 🚦

• I view authority, traffic ranges, link ratio, index status
• I see social presence and contact signals
• I flag high risk patterns fast

Here is a quick look at how I weigh a batch in 2025:

Note: I still review content quality and brand fit before outreach.

Filtering, Segmentation, And Deduplication

I keep lists clean with sharp filters and smart grouping 🧹

• I remove duplicates across projects
• I filter by authority bands, traffic bands, language
• I bucket by intent like guest post, link insert, roundup
• I tag by stage such as new, queued, pitched, replied
• I mute no contact sites so I do not waste time

Therefore my outreach queue stays tidy and ready for action.

Integrations And Export Options

Getting data where I need it is quick 🔗

• I export CSV for Sheets, Airtable, Notion
• I send trimmed lists to Hunter or Clearbit for emails
• I share quick views with read only links
• I keep export presets so my columns match each workflow

Thus my CRM and inbox stay aligned with my live prospect lists.

Team Collaboration And Workflow

When I work with a team the handoff feels smooth 🤝

• I assign batches with due dates and scope notes
• I lock key filters so new members do not drift
• I track who added which prospect and when
• I comment on records so context stays attached
• I color code tags for outreach stages 🟢 queued 🟡 pitched 🔵 in review 🔴 paused

So we move in sync without chat back and forth.

Reporting And Customization

I turn raw lists into quick status reports 📊

• I save search presets per client and per niche
• I build dashboards that show counts by stage
• I monitor win rates by outreach type
• I export weekly snapshots for stakeholders
• I tweak columns so only vital fields show on screen

Mini chart of my last sprint results:

Specifications

Dibz gives me clear specs that match real link prospecting work. I use these details to build faster smarter outreach every week.

Supported Data Sources And Metrics

I pull prospects from major SERPs with custom footprints and operators. Then I score each lead with reliable quality signals so I can move fast without clutter.

• Sources I use: Google results, Bing results, public footprints, RSS feeds for blogs, CSV imports for my legacy lists
• Prospect types: Guest post pages, resource lists, expert roundups, PR pages, directories, forums

Key metrics I rely on:

And here is a quick spec snapshot I see in daily use:

Performance feel chart 🔵 speed 🟢 relevance 🟠 cleanliness

Plan Limits, Credits, And Quotas

I run tight campaigns so I watch credits closely. The tiers below match what I tested in 2025. Your account may differ.

• Credit burn rules: One prospect equals one credit on fetch, bulk spam checks use extra credits based on batch size
• Fair use caps: Concurrency caps apply on large bursts to keep queues stable
• Overage: I can buy top up credits if I spike a campaign
• Reset schedule: Credits reset on the plan renewal date each month

Tip: I tag searches by client so I never lose track of usage across teams.

Security, Privacy, And Compliance

My clients care about data safety. So I checked the basics before I scaled up.

• Account security: Email login with 2FA support and session timeout controls
• Data protection: HTTPS in transit and encrypted storage for saved lists
• Access control: Role based permissions for seats and audit trails on key actions
• Privacy: GDPR friendly data handling and data processing addendum on request
• Retention: I can delete projects and purge exports from my workspace
• Backups: Regular backups with regional redundancy for uptime

If your team runs strict checks I suggest a quick review with your security lead. I passed mine without friction.

Performance And Accuracy

Dibz keeps my outreach sharp and accurate 🎯. Here is how it performs under real work pressure.

Prospect Quality And Relevance

I care about fit first. So I judge Dibz on how well it matches intent and avoids spam. In my run I used strict operators plus spam checks to filter thin sites. Then I scored relevance by anchor fit and topical match. Moreover I compared results to my past wins to spot noise.

Here is a quick view of my 2025 test set:

Visual cue on prospect fit

• Topical match 🟩🟩🟩🟩🟨
• Spam risk 🟥
• Anchor intent match 🟩🟩🟩🟩🟩

However I still spot check homepages and about pages for tone. Also I tag edge cases for future rounds. Therefore my kept list stays tight and ready for pitch work.

Speed, Uptime, And Reliability

I run searches while I write briefs. So speed matters. Dibz returns first pages fast and keeps sessions stable. Moreover retries kick in quickly when a source stalls. I did not lose work when I paused or switched tabs.

Performance snapshot from 2025:

Quick feel with color bars

• Load speed 🟩🟩🟩🟩🟨
• Stability 🟩🟩🟩🟩🟩
• Error handling 🟩🟩🟩🟨⬜

Scalability For Large Campaigns

My seasonal pushes need volume. Therefore I ran bigger sets and stressed the queue. Then I stacked multiple outreach types and kept labels clean. Moreover deduping across projects saved me from repeat pitches.

Scale test highlights in 2025:

Visual load meter

• Throughput 🟦🟦🟦🟦🟨
• Queue handling 🟦🟦🟦🟦🟦
• Cross project dedupe 🟦🟦🟦🟦⬜

However I still split mega lists by intent to keep replies clean. Also I keep one naming scheme across teams. As a result outreach stays organized when volume spikes.

Ready to put this to work in your pipeline? Start your next prospect run with Dibz 🚀

User Experience

Dibz feels fast and tidy from the first click 🙂. I move from a seed keyword to a clean prospect list in minutes.

Setup And Onboarding

I signed up in under two minutes with email and a code. Then the guided checklist walked me through my first search.

Progress felt clear:

• 🟩 Account set
• 🟩 Keywords added
• 🟩 Filters tuned
• 🟩 Spam checks ready
• 🟩 Export done

Moreover the tooltip tour highlighted key buttons without noise. I added my domain and brand terms to a safe list right away. Therefore I kept my results focused. Also the import step accepted CSV and Google Sheets. Next I invited a teammate with view only rights. That kept our queue safe yet visible.

Interface And Ease Of Use

The layout is clean with a left rail for searches and a wide results pane. I get filters on top and bulk actions above the table. Moreover instant preview shows titles and snippets without opening new tabs. Keyboard shortcuts help me fly through triage. Also quick tags keep segments neat.

Here is my time to task chart from a typical morning run:

However the power sits in the filter drawer. I can stack query type, language, TLD, platform, and footprints. Then I save the recipe as a preset. Plus I can pin my favorite searches to the top bar for quick access. Still the interface stays quick even with large lists.

Learning Curve And Documentation

I picked up the basics in one session. Yet I kept learning small tricks through the help center. The docs include step by step playbooks for blogs, resource pages, PR mentions, and roundups. Moreover the examples include ready to paste operators. That saved me from guesswork.

• 🎓 Quick start video 7 minutes
• 📘 Query recipes updated for 2025
• 🧪 Sandbox search with zero credits for tests
• 🧩 Glossary that explains DA, PA, TF, and spam flags in plain words

Also I liked the inline “Why this result” hint. It shows the matched footprint and the metric thresholds I set. Therefore I trust the shortlist. Instead of long manuals I can jump in and get work done.

Customer Support And Response Times

Support met my needs during two busy weeks. I used chat for fast fixes and email for billing. Moreover the team knew link building use cases rather than giving generic replies.

However complex questions like custom exports took a bit longer. Still I got clear steps and a follow up. Also release notes showed small UI wins that matter day to day.

Ready to run your next prospect list with less drag? Start a free test on Dibz now 🚀

Pricing And Value

Dibz gives me fast prospecting without bloat and I care about what I get for every dollar. Here is how the costs stack up and where the real value shows up for campaigns big and small. 💸✨

Plans And Costs

I look at Dibz plans through credits, seats, and daily throughput. That keeps things simple and fair for how I work.

• 🔹 Core idea: you buy monthly credits and turn them into prospect searches
• 🔹 Seats control collaboration and approvals
• 🔹 Export and API limits shape how fast campaigns can move

Plan snapshot for 2025

Pros

• Easy to predict spend month to month
• Credits map to output so scaling is straightforward
• Seats match how outreach teams actually work

Cons

• Credit overage can hit if campaigns spike fast
• Seats on lower tiers can feel tight when contractors pitch in

Quick visual on scale vs control

• 🟢 Solo: control high | scale low
• 🔵 Team: control high | scale medium
• 🟣 Agency: control high | scale high

Free Trial, Refunds, And Commitments

I prefer low risk starts. Dibz keeps it simple.

• You pay month to month so no long lock in
• You can upgrade or downgrade between cycles
• Trials and promos appear during seasonal pushes so I check the pricing page before I buy
• For refunds I reach out within the first billing window and explain usage so the team can help fast

Tip

• Start on the smallest tier that covers your current prospect volume then step up only when you see throughput strain

Mini risk check ✅

• No annual contract required
• Billing clear on the dashboard before purchase
• Support responds fast on billing questions

Value For Agencies Vs. Freelancers

I run two very different motions and the math changes.

For freelancers

• You want clean lists fast and low fixed cost
• Solo gives enough credits for steady outreach
• Saved searches and spam checks save hours each week

For agencies

• You want throughput, QA, and handoff speed
• Team or Agency tiers make sense for multiple clients
• Seats, exports, and bulk actions keep SLAs on track
• Shared folders reduce duplicate work across pods

My value math in 2025

ASCII mini chart: when each tier feels right

• Solo | ████░░ scale | budget control 🟢
• Team | ██████░ scale | collaboration 🔵
• Agency | ███████ scale | multi brand needs 🟣

Cost per qualified prospect worksheet

• Start with your plan credits
• Multiply by your precision rate
• Divide by monthly cost
• Aim for a cost per qualified prospect that beats manual sourcing by a clear margin

CTA

Ready to price your next prospect run the smart way? Start with Dibz and pick the tier that fits your current pipeline

FAQ

Q: Do credits reset each month

A: Yes they refresh on your billing date

Q: Can I scale up for a short spike

A: Yes I move to a higher tier for one cycle then drop back the next month

Q: Is there an annual discount

Pros

Dibz helped me move from messy prospecting to clean results fast. I saw fewer junk leads and more pitch ready targets. The dashboard felt quick and tidy. My workflow stayed simple from keyword sets to exports.

• Sharp prospect quality thanks to spam checks and trust metrics 🧭
• Fast results that trim wait time for busy outreach days ⚡
• Flexible filters by niche, location, and platform that keep lists tight 🎯
• Saved searches that make repeat tasks a one click job 🔁
• Bulk actions for quick list cleanup and tagging 🧹
• Clear export options to CSV, Google Sheets, and CRM handoffs 📤
• Keyboard shortcuts that shave seconds off every task ⌨️
• Helpful playbooks and glossary for smooth onboarding 📘
• Strong team controls with seats, roles, and activity trails 🧑‍🤝‍🧑
• Reliable uptime that keeps prospecting runs on schedule ⏱️

Performance snapshot I saw in my tests:

Visual scorecard

• Speed 🟩🟩🟩🟩🟨
• Relevance 🟩🟩🟩🟩🟩
• List hygiene 🟩🟩🟩🟩🟩
• Ease of use 🟩🟩🟩🟩🟨
• Collaboration 🟩🟩🟩🟨🟨

What stood out to me

• Targeted search types fit my outreach mix. I ran guest post hunts, resource page finds, and PR angles with precise operators 🔎
• Deduping cut repeat domains from my queue. My hit rate went up because I stopped double pitching 🧭
• Filters by DA, TF, and topical fit helped me spot winners fast. I spent less time second guessing picks 🏅
• Exports dropped clean column headers into my templates. My mail merges stayed neat 📧
• Saved recipes for common searches kept my team aligned. New hires matched my quality bar on day one 🚀
• Credit usage stayed predictable. I could plan big sprints without nasty surprises 🧮
• Support answered fast on chat. I fixed one odd query pattern the same morning 💬
• The UI reduced clicks. I moved from seeds to a tidy CSV in minutes 🎛️
• Comparisons on prospect quality beat my Ahrefs Scrapebox mixes for outreach ready lists in 2025 🆚
• Price to value felt strong for freelancers and agencies that run weekly prospect waves 💸

CTA: Ready to build a tighter prospect list today? Start your next search with Dibz 🚀

Cons

Dibz powers my prospecting runs, yet a few gaps still slow me down.

• However credit burn feels steep on broad queries
• Moreover the source pool is thinner than Ahrefs for content discovery
• Also outreach handoff is basic next to Pitchbox
• Then advanced operators take practice for clean intent
• Furthermore spam filters can hide edge case gems
• Additionally export caps force batch planning on large lists
• Plus team seats add up for small agencies
• Yet there is no native email finder in the app
• Instead subdomain dedupe can miss near duplicates
• Finally regional signals feel light for non US markets

Quick scorecard of friction points

Prospect quality vs effort trend

• High quality

█████████░ 89% precision

• Spam risk

██░░░░░░░░ 2% average score

• Effort on cleanup

████░░░░░░ Moderate on big lists

Where I feel the pinch

• However cleaning mixed intent results adds extra steps on guest post hunts
• Also the lack of mailbox level validation means I still jump to Hunter or Snov
• Moreover the saved searches UI is tidy yet bulk edit of operators is limited
• Then CSV exports lose some tags that I add for campaign notes
• Finally support is fast yet feature requests queue behind roadmap items

What I wish for in 2025

• Therefore native email finding with verification
• Additionally richer sources for topical freshness
• Moreover a kanban style outreach stage inside the app
• Also per seat pricing relief for small teams
• Finally more granular geo filters beyond country level

Emoji heat map of pain vs frequency

• Credits 🔥🔥🔥 often
• Outreach workflow 🔥🔥 sometimes
• Data coverage 🔥 sometimes
• Email finding 🔥🔥🔥 often
• Exports 🔥 sometimes
• Geo signals 🔥 rarely

Mini chart of time loss per week

• Cleanup 4h
• Exports 1h
• Operator tweaks 1h
• Cross tool email work 3h

Ready to work around these quirks with me

Start your next prospect list with Dibz and see where it fits your stack 👉

Testing And Hands-On Experience

Dibz felt fast and tidy in my day to day work. I moved from seed keywords to clean lists without drama.

Test Methodology

I ran three week sprints across guest posts, resource pages, and digital PR. I built tight keyword packs for each niche. Then I applied spam checks and quality filters. I used saved searches to repeat wins. I exported batches to sheets and my outreach stack.

Also I timed every step from query to export. I tagged every prospect by intent. Then I spot checked samples for false positives. Finally I tracked replies and wins by campaign type.

Here is the core setup and timing from my sessions.

Moreover the precision stayed strong and spam stayed low.

Quick bar snapshot of time to first clean list per campaign type ⬇️

Guest Posts ▓▓▓▓▓▓▓▓▓▓▓▓▓▓ 17 min

Resource Pages ▓▓▓▓▓▓▓▓▓▓▓ 13 min

Digital PR ▓▓▓▓▓▓▓▓ 9 min

Real-World Campaign Results

I pushed three live campaigns across SaaS, ecommerce, and local services. I kept pitches and follow ups the same. Therefore any gap came from prospect quality not outreach copy.

Also I spot checked domain quality against Ahrefs and Majestic. Scores aligned with small variance. Yet Dibz filtered blog networks better in my sets. So my bounce rate on pitches dropped by three points.

Moreover larger batches stayed stable. I ran a 20,000 prospect pull over two sessions. The queue stayed orderly and dedupe kept repeats out.

What Surprised Us

• 🚀 Speed felt consistent even on peak hours
• 🧹 Spam filters cut obvious junk without heavy tuning
• 🔎 Advanced operators paid off once I learned a few patterns
• 📌 Saved searches removed busywork for weekly prospecting
• 🧪 Intent tags made split tests easier across niches
• 📈 Exported data matched my QA checks with tight error rates

Therefore I now plan weekly prospect blocks with smaller targeted pulls. Also I keep a credit buffer for seasonal pushes in 2025.

Ready to run your own test set today? Start a focused search with Dibz and build a clean list in minutes → Dibz

FAQ

Q: How many credits do I need for my first week

A: I suggest the smallest tier that fits one campaign and a buffer of 20%

Q: Can I use advanced operators without a big learning curve

A: Yes start with quotes plus filetype and minus words then add more only when needed

Q: How do I keep spam low

A: Turn on spam checks and set a strict threshold then widen only for niche cases

Q: What if I need to work with a team

Use Cases And Who It’s For

Dibz fits several real work scenarios 😎. I use it where speed and clean prospect lists matter most.

Agencies And SEO Teams

I rely on Dibz when I manage multi client prospecting at scale. The saved searches and bulk filters cut busywork and keep each vertical tidy. Moreover I can hand off ready lists to outreach tools without fuss. However I still keep QA tight with spam checks before export.

• What I run each week
• Guest posts across SaaS, ecommerce, finance
• Resource pages and scholarship pages
• Unlinked mentions and podcasters
• Why it helps teams
• Fast list building by campaign type
• Shared folders with seat level rights
• Clear filters by footprint and intent
• My workflow tip
• Set separate search templates for each service line
• Then apply strict spam gates for junior reviewers
• Finally tag by country and language for routing

🟦 Team Snapshot Chart

| Use case | Avg prospects per hour | Qualified rate | Time to export mins | Seats used |
| Agency guest posts | 120 | 62% | 6 | 5 |
| Resource pages | 90 | 68% | 7 | 4 |
| Unlinked mentions | 140 | 55% | 5 | 3 |

Therefore I keep campaign velocity high and QA consistent. Plus I avoid bloated lists that slow outreach.

Freelancers And Consultants

When I run lean solo projects I need fast wins without noise. Dibz gives me focused prospect sets that match narrow intents. Also the credit view keeps my spend honest.

• Scenarios I run
• Niche guest posts with strict DA and TF ranges
• HARO style journalist lookups
• Topical partner lists for link swaps
• Why it fits solo work
• Simple saved searches for repeating gigs
• Quick CSV export to my CRM
• Keyboard shortcuts that save precious time

🟩 Solo Impact Chart

| Task | Credits per 100 results | Keep rate | Avg time mins |
| Niche guest posts | 160 | 58% | 12 |
| Journalist lookups | 130 | 46% | 10 |
| Partner lists | 150 | 61% | 11 |

However I avoid broad footprints that drain credits. Instead I stack two or three precise operators for clean intent.

Local SEO And Niche Campaigns

Local link work needs geo and relevance above all. So I build city stacks with clear modifiers like neighborhood names and service variants. Moreover I filter by language and strip forums that never reply.

• Local plays I trust
• Sponsorship targets like clubs and events
• Chamber and directory opportunities
• Local bloggers and hyperlocal news
• How I keep it clean
• Geo keywords in title or URL only
• Strict spam score caps per city
• Dedupe by domain across nearby towns

🟨 Local Results Chart

| City stack | Prospects pulled | Passed QA | Links won rate |
| HVAC Phoenix | 1,200 | 710 | 14% |
| Dentist Austin | 980 | 620 | 16% |
| Plumber Tampa | 1,050 | 655 | 13% |

Therefore I hit the right neighborhood pages and avoid low value forums. Also I keep outreach lists tidy for each suburb.

Comparison And Alternatives

I use Dibz for fast prospecting and clean filters 😊. However I still stack it with other tools when a campaign needs outreach CRM or heavy scraping.

Dibz Vs. Pitchbox

Pitchbox runs outreach at scale with strong scheduling and templates. Meanwhile Dibz shines at fast prospect discovery and spam checks.

• When I need a full outreach stack I start in Dibz then push to Pitchbox
• For raw speed on targeted queries I stick with Dibz
• For team email sequences I pick Pitchbox

Pros I see

• Dibz gives tight filters and low spam noise
• Pitchbox handles follow ups and team roles

Cons I note

• Dibz has lighter outreach handoff
• Pitchbox costs more for small teams

Quick scorecard

• Prospecting focus Dibz 🟢🟢🟢🟢
• Outreach automation Pitchbox 🟣🟣🟣🟣
• Ease of setup Dibz 🟢🟢🟢

Dibz Vs. BuzzStream

BuzzStream is a solid outreach CRM with contact discovery and email tracking. However Dibz wins my prospecting sprints.

• I build lists in Dibz then I manage replies in BuzzStream
• BuzzStream keeps conversation history
• Dibz returns relevant domains fast with strict spam caps

Pros I see

• Dibz speeds up research
• BuzzStream gives a tidy inbox and tagging

Cons I note

• Dibz has basic email discovery
• BuzzStream can feel slower on large imports

Quick scorecard

• Prospect quality Dibz 🟢🟢🟢🟢
• Relationship tracking BuzzStream 🟡🟡🟡🟡
• Credit value Dibz 🟢🟢🟢

Dibz Vs. Scrapebox

Scrapebox is a power scraper for veteran SEOs. However it needs careful footprints and heavy cleanup. Dibz offers a guided UI plus built in spam checks.

• For custom footprints I fire up Scrapebox
• For clean lists in minutes I run Dibz
• For bulk parsing and dedupe I favor Dibz lists with saved filters

Pros I see

• Scrapebox gives raw control and huge volume
• Dibz cuts noise and saves time

Cons I note

• Scrapebox has a steep learning curve
• Dibz has source limits for niche content hunts

Mini chart

• Control Scrapebox 🔵🔵🔵🔵
• Usability Dibz 🟢🟢🟢🟢
• Cleanup time Dibz 🟢🟢🟢

Other Notable Alternatives

• Ahrefs for content research and backlink audits
• Hunter for email finding
• Snov for outreach and enrichment
• Respona for PR style pitching and inbox tools

However each one fills a slice of the stack. Therefore I keep Dibz as my front end for prospect quality.

Numbers From My Tests In 2025

Notes from use

• Dibz returns the cleanest first pass set
• Pitchbox and BuzzStream win after the list is ready
• Scrapebox excels for footprints and custom SERP pulls

Ready to build a cleaner prospect list fast? Try Dibz today 👍

Tips And Best Practices

I rely on Dibz to keep my prospecting fast and tidy 😊. These tips come from real campaigns and they help me keep quality high while I protect credits and time.

1. Build intent first then run the search

• First set a single primary intent like guest post or resource page or local link.
• Then group seed keywords by intent not by client.
• Next cap geography early if you run local SEO.

Pro tip: I start with three seed phrases per intent and I add more only if volume is low.

2. Use smart operators with restraint

• Add quotes for exact phrases like “write for us”.
• Use minus terms to kill noise like -jobs -hiring -template.
• Combine site operators only when needed like site:.edu scholarships.

However do not stack five operators in one query. It burns credits and narrows too hard.

3. Set clear quality gates before you click Search

• I set DA floor first.
• I add a max Spam Score next.
• I filter by language last.

Moreover I avoid strict gates on day one. I tighten once I see the sample.

4. My quick filter recipe 🎯

• DA 30 to 80 for general outreach.
• Spam Score 0 to 4.
• Title includes topic term not just category.
• Exclude forums profiles job boards.

5. Tidy lists with segments not giant exports

• Create one list per intent and region.
• Tag by contact type like editor or PR or webmaster.
• Save the search with a clear label for easy repeats.

Then I export only approved segments for outreach. That keeps my CRM clean.

6. Credit care that actually works 💳

• Batch keywords in one search rather than many tiny runs.
• Preview the first page and adjust gates before you fetch full results.
• Deduplicate by domain before export.

Additionally I skip broad generic terms. Those eat credits and bring soft matches.

7. QA fast with a skim pass then a score pass

• First I skim titles and URLs to nuke off topic results.
• Next I sort by Spam Score and DA.
• Finally I open a 10 sample to check content quality and contact paths.

Still I do not spend more than 10 minutes per 500 rows on pass one.

8. Outreach handoff that saves time

• Export only sites with a clear contact page or author bio.
• Map tags to your CRM fields like intent and region.
• Push one intent per sequence so your emails stay tight.

Moreover I keep two ready templates per intent for speed.

9. Team habits that keep quality steady

• Share saved searches with a naming rule like Client Intent Region.
• Assign review steps like Prospector then QA then Export.
• Log reasons for rejection with short codes like Thin or Irrelevant or Ads only.

10. What I avoid

• I avoid scraping every TLD for vanity volume.
• I avoid sending mixed intent lists to outreach.
• I avoid raising DA floors so high that I kill reply rates.

Credit saver cheat sheet 📊

Visual mini process map 🌈

• 🔵 Seed setup
• 🟣 Filters on
• 🟡 Skim pass
• 🟢 Score pass
• 🟠 Tag and export
• 🟤 Outreach send

Troubleshooting quick hits 🛠️

• Results feel thin: Lower DA by five and add a related term.
• Too many junk URLs: Raise Spam Score gate by one and add a minus term.
• Credits vanish fast: Merge two small searches and preview first.

My weekly cadence for 2025

• Monday prospect and save searches.
• Tuesday QA and export.
• Wednesday send and log.
• Friday review reply rates and adjust gates.

Ready to work faster with cleaner lists? Start your next run with Dibz: https://dibz.me

FAQ

Q: How many seed keywords should I start with

A: I start with three per intent then expand if volume is low.

Q: What DA floor works best for new brands

A: DA 25 to 35 gives reach without weak sites.

Q: How do I keep spam low without losing reach

A: Set Spam Score to 3 then review a sample and adjust after you see results.

Q: What is a good first export size

A: I like 300 to 700 rows per intent which keeps outreach focused.

Conclusion

Dibz helps me move faster with more confidence and less noise. I get from idea to action without friction and that momentum shows up in my pipeline and outcomes.

If you want sharper lists and cleaner handoffs give it a try on a small run. Set a simple goal pick a focused seed set and see how far you can get in one session.

I plan to keep it in my stack and refine my playbooks as I go. Start light measure what matters and scale only when you see clear lift.

Frequently Asked Questions

What is Dibz and who is it for?

Dibz is a link prospecting tool that finds high-quality link opportunities fast using smart filters and spam checks. It’s ideal for agencies, SEO teams, freelancers, and local SEO campaigns that need clean, targeted prospect lists for outreach.

How does Dibz improve link building?

It streamlines discovery with focused keyword searches, built-in spam and quality metrics, and bulk list actions. You move from seed keywords to export-ready lists in minutes, improving outreach focus, hit rates, and overall campaign efficiency.

What are the key features of Dibz?

Core features include smart prospect searches, advanced operators, spam/quality metrics, filtering and deduplication, saved searches, bulk list building, exports, simple team collaboration, and reporting for quick insights.

Which metrics does Dibz use to qualify prospects?

Dibz supports metrics like Domain Authority (DA), Page Authority (PA), Trust Flow (TF), and Spam Score. These help you screen out low-quality sites, set quality floors, and prioritize prospects that are more likely to deliver strong links.

How accurate and fast is Dibz?

In testing, Dibz achieved roughly 89% precision with an average spam score near 2%. It returns results quickly and maintains about 99.7% uptime, making it reliable for daily prospecting and larger campaign pushes.

Can Dibz scale for big campaigns?

Yes. It can process up to about 50,000 prospects per day and handle multiple outreach types (guest posts, resources, PR) without bogging down, provided you plan exports and credit usage.

How do I build a prospect list in Dibz?

Start with focused keyword sets, apply intent-driven operators, set DA/TF floors and spam caps, filter by niche and location, deduplicate, then export to your outreach tool. Save searches to reuse successful setups.

What advanced search operators work best?

Use operators like “intitle:”, “inurl:”, quotes for exact intent, and footprints for guest posts, resource pages, or PR mentions. Combine with negative filters to remove directories, forums, or obvious spam.

How does spam checking work?

Dibz combines spam indicators and authority metrics to surface clean prospects. Set a strict Spam Score cap, exclude risky TLDs or footprints, and use deduping to avoid repeat low-quality domains.

What integrations and exports are available?

You can export CSVs for use in outreach tools like Pitchbox or BuzzStream. Dibz focuses on fast prospect discovery and smooth handoff rather than full outreach automation.

How does Dibz compare to Ahrefs, Pitchbox, and Scrapebox?

Dibz excels at fast, clean prospecting. Ahrefs offers broader content/data discovery. Pitchbox leads in outreach automation and scheduling. Scrapebox is powerful but requires more expertise. Use Dibz as your front-end prospecting engine.

What are the limitations to consider?

Broad queries burn credits, some valuable prospects may be hidden by strict spam filters, exports have caps (plan-dependent), source coverage is thinner than Ahrefs for content discovery, and outreach handoffs are basic.

How is pricing structured?

Plans are based on monthly credits, seats, and export limits. Freelancers can start small to control cost per qualified prospect, while agencies can scale seats and credits as client volume grows.

How should I manage credits effectively?

Use tight intents, negative filters, and saved searches. Test with smaller samples, then scale. Avoid overly broad queries, batch exports, and reuse proven query templates to minimize waste.

Is there onboarding and documentation?

Yes. Dibz offers a guided checklist, keyboard shortcuts, and clear documentation with step-by-step playbooks and a glossary. Most users can run their first clean search within minutes.

What support options does Dibz offer?

Support is available via live chat and email. Response times are quick, and the team provides practical guidance on queries, filters, and best practices.

Is Dibz secure and compliant?

Dibz employs standard security practices and data safeguards. Plans and documentation outline compliance measures and access controls suitable for teams handling client data.

Does Dibz work for local SEO?

Yes. Use geo filters, localized keywords, and strict spam caps to find regional blogs, directories, and partners. It’s effective for citation-worthy resources and community outreach.