Marketing Analytics and Reporting
Reporting that answers real questions. We define KPIs, build reliable engagement datasets from Marketing Cloud and CRM, and set up measurement you can defend.
Most marketing teams have plenty of numbers and little agreement on what they mean. Opens are inflated by mail client privacy features, click rates are calculated three different ways, and revenue attribution depends on which spreadsheet you open. Reporting becomes a monthly argument instead of a tool for deciding what to do next.
GeekMidst helps teams using Marketing Cloud Engagement, Account Engagement and Salesforce CRM build reporting that is consistent, explainable and tied to decisions. We define the measures, build the datasets behind them and set up dashboards in the tools you already have.
Who this is for
- Marketing leaders who need a clear view of programme performance and what is actually driving pipeline or revenue.
- Marketing operations teams spending too much time exporting tracking data and rebuilding the same reports by hand.
- Analysts and data teams who need clean, well-documented engagement data from Marketing Cloud for their own models.
Questions we help you answer
| Question | Typical measures | Usual data source |
|---|---|---|
| Are our emails reaching people? | Delivery, bounce and complaint rates by domain | Marketing Cloud data views and tracking |
| Which programmes engage? | Unique clicks, click-to-send rate, unsubscribes per send | Data views joined to journey and send metadata |
| Are journeys working as designed? | Entry, exit and goal counts per path | Journey and send data, plus journey analytics |
| Does marketing influence pipeline? | Campaign influence and conversion by stage | CRM campaigns and opportunities |
| What would have happened anyway? | Lift against a holdout group | Controlled test design plus outcome data |
What we do
KPI definitions
A short, agreed list of measures with exact definitions, so a click rate means the same thing in every report.
→Engagement datasets
Scheduled SQL queries on Marketing Cloud data views that build clean reporting data extensions before tracking data ages out.
→CRM campaign reporting
Campaign hierarchies, member statuses and influence reporting connected to marketing activity.
→Dashboards
Reports and dashboards in Salesforce, CRM Analytics, Tableau or your BI tool, built on the datasets above.
Measurement design
Holdout groups, baselines and test plans for programmes where you need to know the incremental effect.
Example: a 30-day send performance dataset
The query below runs as a Query Activity in Automation Studio and writes to an assumed target data extension Email_Performance_30d_DE with JobID as primary key. It aggregates each data view in a subquery before joining, which avoids the row multiplication you get from joining raw event tables. Data views keep only a limited history, so check the current retention period in Salesforce Help and schedule the query accordingly. Treat it as a starting point, not production code.
SELECT
j.JobID,
j.EmailName,
s.Sends,
ISNULL(c.UniqueClickers, 0) AS UniqueClickers,
ISNULL(u.Unsubscribes, 0) AS Unsubscribes
FROM _Job j
INNER JOIN (
SELECT JobID, COUNT(*) AS Sends
FROM _Sent
WHERE EventDate >= DATEADD(day, -30, GETDATE())
GROUP BY JobID
) s ON s.JobID = j.JobID
LEFT JOIN (
SELECT JobID, COUNT(DISTINCT SubscriberKey) AS UniqueClickers
FROM _Click
WHERE EventDate >= DATEADD(day, -30, GETDATE())
GROUP BY JobID
) c ON c.JobID = j.JobID
LEFT JOIN (
SELECT JobID, COUNT(DISTINCT SubscriberKey) AS Unsubscribes
FROM _Unsubscribe
WHERE EventDate >= DATEADD(day, -30, GETDATE())
GROUP BY JobID
) u ON u.JobID = j.JobIDHow an engagement runs
- 01
Agree the questions
Start with the decisions reporting should support, then pick the few measures that inform them. Vanity metrics are dropped early.
- 02
Audit current reporting
Review existing reports, tracking settings, campaign structures and the data available, and note where numbers disagree and why.
- 03
Build the data layer
Create the queries, data extensions, CRM fields and campaign structures needed, with retention and refresh schedules documented.
- 04
Build dashboards
Produce dashboards for each audience, from executive summaries to operational views for the marketing operations team.
- 05
Reconcile and hand over
Check figures against source systems, document definitions and walk your team through maintaining and extending the reports.
Dependencies and honest limits
Good reporting relies on consistent naming, correct campaign associations and tracking that is switched on and tested. Where those are missing we will say so and fix them first. Some things cannot be measured precisely: open data is unreliable for many recipients, and multi-touch attribution models are assumptions, not facts. For questions about incremental impact, a holdout group usually tells you more than any attribution model. If your deliverability numbers look wrong, our email deliverability consulting is often the better first step.
Questions we hear
Should we still report open rates?
Do we need a separate BI tool?
How do we keep tracking history beyond data view retention?
Can you build attribution for us?
Want reporting your team agrees on?
Tell us what you report today and which decisions it should support, and we will suggest where to start.
