One report per client across PR, ABM, paid, content and social.
We build the data model and the dashboard. Your account leads review instead of build. For integrated B2B tech agencies whose reports have to put PR metrics next to funnel metrics, and whose every client runs a different CRM.
Last updated October 2026
The problem
Sound familiar?
Every client has a different CRM
HubSpot here, Salesforce there, Marketo next door. Separate credentials, different objects, different stage names, a different definition of an MQL.
PR and pipeline live in different decks
Placements come from Muck Rack or a coverage log. Sourced pipeline comes from the CRM. Nobody has them in one story per client.
Each practice reports its own way
Paid uses one tool, social another, PR a spreadsheet. The weekly looks different depending on who built it.
The monthly eats a week per account lead
Eight practices, five to twelve platforms, one deck. The account lead builds it by hand and the client still asks what changed.
How B2B Agency Reporting fixes it
We build one standard data model across all eight practices, with placements, outlet tier, hashed contacts and funnel stages as first-class fields. Every client's CRM maps into the same stage names. Metric definitions live in code. Claude drafts the headline. Your account lead edits it and sends one report per client, on your domain.
What changed in 2026?
In 2026 B2B buyers ask ChatGPT and Perplexity which vendors to shortlist, and clients ask their agency why the AI answer did not name them. So a B2B agency report now carries AI visibility reporting next to the 6sense reporting dashboard view and the ABM reporting it always had: tracked buyer questions, which brands and URLs each answer cites, citation share, and the week-over-week change.
What's included?
- Read-only, least-scope credentials per client per source, including each client's CRM
- One standard model across PR, analyst relations, ABM, paid, web, AI search, content, social and deliverables
- Daily snapshots of CRM stages and 6sense buying stages, because stage history is often not tracked
- Branded dashboard on your domain, one login per client, weekly status and monthly performance on schedule
- AI-drafted headline and anomaly flags, approved by your account lead before anything sends
- AI search visibility panel from scheduled AI Overview captures and the tracking tools you already pay for
- A mapping table with an owner and a review loop, so the model stays true when campaign names drift
- Handover docs and training, plus a maintenance plan for connector fixes
Why it is harder
Why is B2B agency reporting harder than B2C?
Because the report ends at the client's CRM, and every client has a different one. Three things follow from that.
Few buyers, big deals
Marketing is judged on pipeline
A buying committee, sales cycles from weeks to 18 months, and a handful of target accounts. So the report has to end at the CRM, and the CRM belongs to the client.
One CRM per client
Every client is a separate integration
Separate credentials, different objects, different stage names and a different definition of an MQL. HubSpot for one, Salesforce for the next, Marketo for the third.
PR next to pipeline
Placements and funnel stages in one story
An outlet tier and a message hit are judgment calls. A sourced opportunity is a CRM row. The report has to hold both as first-class fields and tell one story per client.
The practices
What does each practice report, and from where?
Eight practices, one row each, with the metrics and the usual sources. All of them map into one model, so PR placements sit next to sourced pipeline in the same report.
| Practice | What it reports | Usual sources |
|---|---|---|
| PR and analyst relations | Placements, outlet tier, share of voice against competitors, message pull-through, referral traffic and backlinks, analyst briefings and report inclusions. Tier and message hit are judgment calls, so the model stores them as fields a person sets. | Muck Rack, Cision, Meltwater, plus a hand-kept coverage log |
| ABM and demand gen | Target accounts reached, engagement by buying stage, 6QA or equivalent qualified accounts, MQL, SAL, SQL, opportunities, marketing-sourced pipeline. | 6sense, Demandbase, RollWorks, the client's CRM |
| Paid media | Spend vs pacing, impressions, CTR, CPL, CPA, leads by campaign and channel, cost per opportunity. | LinkedIn Ads, Google Ads, Reddit Ads, Microsoft Ads, DSPs |
| Web and SEO | Sessions, conversions, top pages, organic clicks and positions, Core Web Vitals. | GA4, Search Console, Semrush or Ahrefs |
| AI search visibility | Tracked buyer questions, which brands and URLs each AI answer cites, citation share, week-over-week change. For ChatGPT and Perplexity there is no direct feed that fits a client report, so we use the tracking tools. We do not invent a feed. | Scheduled Google AI Overview captures we run, plus Profound, Peec, Scrunch or Nightwatch through their API or export |
| Content | Pieces published, pipeline of drafts, views, downloads, conversions per asset. | CMS, GA4, project management tool |
| Social | Follower growth, engagement rate, top posts, executive profile performance. | Sprout Social, Hootsuite, Metricool, LinkedIn Page analytics |
| Design and web deliverables | Status from the project management tool and time from the time tracker, so the same report can show margin per client if you want it. | Asana, Monday, ClickUp, Teamwork, Harvest, Everhour |
One model across all of it
How does one data model hold PR, ABM, paid and pipeline?
In five layers. Raw rows at the bottom, a standard model with placement, contact (hashed) and funnel stage as first-class entities, metric code in the middle, the dashboard and the AI on top.
- 05
AI on top
Claude, through the API, does three jobs. It suggests mappings for unmatched names, flags numbers that break pattern, and drafts the plain-language summary of what changed and why.
A person approves the uncertain mappings. The account lead edits the summary. Every number comes from the code. A person approves before anything reaches a client.
- 04
Dashboards and reports
A branded dashboard on your domain, one login per client, plus a scheduled PDF or link report with the account lead's commentary block.
If your team already lives in Power BI, Looker or Tableau, we feed that tool the clean model and you keep the tool.
- 03
Metric definitions in code
CPL, MQL rate, pipeline sourced, placement tier, engagement rate. Each has one formula and one owner.
Every number traces back to a source row. The same question gives the same answer no matter who asks or which client it is about.
- 02
Standard model
One set of entities, defined once: client, account, campaign, channel, content asset, placement, contact (hashed), funnel stage.
Every source maps into these tables. One vocabulary. A HubSpot "Sales Qualified Lead" and a Salesforce "SQL" both become the stage sql. Campaign names are parsed by a naming convention the agency enforces from now on, with a mapping table for the old names.
- 01
Raw layer
Scheduled pulls from each source, per client, each with its own read-only credential.
Rows land exactly as they came, timestamped and tagged with their source. Nothing is cleaned on the way in. Things that change get a daily snapshot, like CRM stages and 6sense buying stages. Ad platform data is pulled again for the trailing 30 days, because platforms restate numbers for days after the fact.
Aggregation is plumbing. Standardization is the product.
Every number is calculated by code and traces back to its source. AI handles the mapping and the write-up, and a person approves it.
The same build, for agencies without the PR and ABM layer, is written up on custom client reporting dashboards.
Why we have a mapping layer
What makes standardization hard across B2B clients?
Four things, and each one has a rule in the model. Identity is the big one for ABM: the same company is a domain in 6sense, a company name in LinkedIn and an account record in the CRM.
Definitions
Every client defines an MQL differently. The model holds the client's definition and the agency's definition side by side, so both numbers are right and both are labelled.
Identity
The same company is a domain in 6sense, a company name in LinkedIn and an account record in the CRM. Domain is the join key. A manual match table catches the rest.
Time
Time zones, week boundaries, currency and attribution windows. One rule for each, written down, applied to every source the same way.
Drift
Campaign names mutate, APIs change and new sources arrive. The mapping layer has an owner and a review loop, so the model stays true after launch.
The weekly
What goes in a standardized weekly for an integrated client?
Nine sections. The headline is the only part a person writes from scratch, and AI drafts even that from the rows below it.
| Section | Each week | Sources |
|---|---|---|
| Headline | Three lines: what moved, why, what we are doing about it | Account lead writes it. AI drafts it from the rows below |
| Pipeline and funnel | MQLs, SQLs, opportunities created. Marketing-sourced pipeline. Target accounts engaged | Client's CRM and marketing automation |
| Paid and programmatic | Spend vs pacing, impressions, CTR, CPL, leads. Target accounts reached by buying stage | 6sense, LinkedIn Ads, Google Ads, Reddit Ads, DSP |
| Web | Sessions, conversions, top landing pages, organic clicks. AI answer visibility on tracked prompts | GA4, Search Console, AI visibility tool |
| Content | Published, in progress, early performance of last week's pieces | CMS, GA4, project management tool |
| Social | Follower growth, engagement rate, top posts, exec post performance | Sprout Social or Hootsuite, LinkedIn Page analytics |
| PR | Placements with outlet and tier, pitches out, rapid-response hits, next week's calendar | Media monitoring tool plus the coverage log |
| Design and web deliverables | Status table: deliverable, owner, due date, status | Project management tool |
| Next week and asks | Approvals, access, subject matter experts needed from the client | Account team |
Weekly rankings and weekly PR counts are mostly noise. A good weekly reports activity there and saves outcomes for the monthly. Reports differ by account lead today because each practice has its own tool and its own definitions. The standard model fixes that. The cadence behind this, weekly for status and monthly for performance, is on client reporting automation for agencies.
Data sources
What do you connect to?
Anything with an API, an export or a database. API first. Scheduled exports second. Browser capture last, with permission.
- CRM and marketing automation
- HubSpot, Salesforce, Marketo, Pardot, Eloqua
- ABM and intent
- 6sense, Demandbase, RollWorks
- Paid and programmatic
- Google Ads, Microsoft Ads, LinkedIn Ads, Meta, TikTok, Reddit Ads, StackAdapt, DV360, The Trade Desk
- Web and SEO
- GA4, Google Tag Manager, Search Console, Semrush, Ahrefs, Hotjar, Microsoft Clarity
- AI search visibility
- Scheduled AI Overview captures, Profound, Peec, Scrunch, Nightwatch
- Social
- Sprout Social, Hootsuite, Metricool, LinkedIn Page analytics, Meta Graph API
- PR
- Muck Rack, Cision, Meltwater
- Content and CMS
- WordPress, HubSpot CMS, Webflow, Google Docs
- Project management and time
- Asana, Monday, ClickUp, Teamwork, Harvest, Everhour
- Call tracking and email
- CallRail, Klaviyo, Mailchimp
- Data connectors, when the long tail of ad platforms is cheaper to buy than to build
- Supermetrics, Funnel, Improvado, Windsor.ai, Fivetran, Airbyte
MCP servers
As of October 2026, Google Ads, Google Analytics, Meta Ads, HubSpot, Salesforce, Semrush, Ahrefs, Supermetrics, Improvado, Meltwater and 6sense each publish an official MCP server. LinkedIn Ads, Google Search Console, Cision, Muck Rack and Sprout Social do not, as far as we have found, and run on their APIs. None of this changes how the pipeline runs. It changes what our engineers and your team can ask in chat.
Your clients' data
How do you handle our clients' data?
It stays in your cloud, under your logins, and we pull aggregates wherever we can. Five promises.
- 01
Your data stays in your cloud, under your logins.
The database, cloud accounts and secrets vault sit in your organization. Our engineers are invited members you can remove in one click.
- 02
We pull aggregates wherever we can and hash anything personal at the door.
A report never needs a person's name. We keep a hashed contact ID, company, stage, dates and source fields, and drop names, emails and phone numbers. We never pull notes, email bodies, call recordings or attachments.
- 03
Two or three named engineers, read-only, every access logged.
One credential per client per source, least scope, revocable on its own. Named accounts with MFA. Production and development are separated, and development runs on masked data. Audit logs are kept 12 months.
- 04
Claude never sees a contact row.
The model gets aggregates and anonymized tables. It drafts commentary and proposes field mappings. A person approves. It holds no write credentials. Anthropic does not train on API inputs and outputs by default.
- 05
We sign your NDA and a data processing agreement.
The agreement names every sub-processor, including any connector vendor in the pipeline. We tell you plainly which certifications we hold and which we do not.
The detail behind them, with data tiers, residency, retention and the incident runbook, is on custom client reporting dashboards.
Timeline
How long does a B2B agency reporting build take?
Most take 4 to 8 weeks, because of the number of sources and the CRM mapping per client. Access is the critical path, so pilot clients and credentials get settled in week one.
Week 1
Scope and access
- NDA signed, written scope with a fixed price
- Pilot clients picked and their credentials settled, because access is the critical path
- Read-only, least-scope credentials per client per source
Weeks 2 to 6
Build
- Raw layer, standard model, metric code, dashboard
- First working slice on real data by the end of week three
- CRM mapping per client, PR and ABM fields added to the model
Weeks 6 to 8
Test and hand over
- Test run on three pilot clients against last month's decks
- Fixes, handover docs and training for the mapping owner
- Reports run on schedule, maintenance plan starts
What does it cost, and who is it not for?
Our standard custom dashboard builds run $12,000 to $18,000 up front plus about $4,000 a year for upkeep, which covers hosting and connector fixes when platforms change their APIs. A B2B integrated build adds a standardization layer, CRM and ABM sources and an AI layer, so it usually lands above that range. This is a typical range. The number is fixed in writing after a one to two week Discovery or after we read your documented data flows.
Who this is not for: agencies under about 40 to 50 client accounts. At that size AgencyAnalytics or Whatagraph is usually the better call, and we say so on the call. The math is on our AgencyAnalytics comparison. The proof for the standardization layer is AutoCar Intelligence, and the proof for automated exports replacing decks is BillboardIQ.
How it works
01.
Scope
Week one. NDA, access, pilot clients and a written scope with a fixed price. Credentials settled first.
02.
Build
Weeks two to six. Raw layer, standard model, metric code, dashboard. First working slice on real data by the end of week three.
03.
Test
Three pilot clients. Your account leads compare the new numbers to last month's decks and we fix every gap.
04.
Handoff
Reports run on schedule. Your team reviews and sends. We keep the connectors and the mapping table current.
Proof it works
What we have already shipped
Case study
AutoCar Intelligence
Nine-plus repair shops unified into one source of truth, every metric recalculated in code
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Find out how many leads are going cold before your team ever sees them
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The offer
Free 30-minute intro call
We listen first. No pitch decks.
Book an intro call
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