This demo shows every step: the data we need, how we analyze it, how scores are calculated, and how recommendations are made.
Acme Apparel
Jan 2022 – Dec 2023 (24 months)
Brand Growth Index
↑ 8 vs last 6 months
Top Recommendation
Improve Paid Search Efficiency
Confidence
75%Good
Just monthly numbers. Nothing more.
| Column | What it tells us |
|---|---|
| Month | The month of your data |
| Revenue | Total revenue generated |
| Orders | Total number of orders |
| New Customers | Number of first-time customers |
| Returning Customers | Number of repeat customers |
| Meta Spend | Amount spent on Meta ads |
| Google Spend (Non-Brand) | Amount spent on Google ads for non-brand keywords |
| Google Spend (Brand) | Amount spent on Google ads for your own brand name |
| Email Revenue | Revenue driven by email campaigns |
| WhatsApp Revenue | Revenue driven by WhatsApp messages |
| Organic Revenue | Revenue from unpaid search and organic traffic |
| Direct Revenue | Revenue from visitors who came directly to your site |
| Google Branded Searches | Google searches that include your brand name |
| Amazon Branded Searches | Amazon searches that include your brand name |
Why this is enough
See an example?
You'll see real data in the demo dashboard.
Needlwork only needs monthly marketing numbers.
We follow a proven process to turn your numbers into insights.
01
Collect
We read your monthly data and organize it.
02
Validate
We check for missing values and inconsistencies.
03
Attribute
We assign revenue to the channels that influenced it.
04
Analyze
We evaluate trends, efficiency, and demand across all channels.
05
Generate Insights
We convert everything into comparable scores on a 0-100 scale.
06
Generate Recommendations
We surface the actions that will drive the most impact.
Needlwork evaluates channels by how spend and revenue actually move together over time, alongside how every other channel is performing in the same periods, before estimating each channel’s contribution.
Customer journey example
A customer sees a Meta ad, visits your site, and buys.
Meta Ads
Website Visit
Purchase
Needlwork does not credit Meta simply because it appeared in this journey.
Our attribution approach
Result: Contribution estimates based on evidence of real impact, not just presence in the journey.
Why it matters
A channel showing up right before a purchase doesn’t mean it caused the purchase. Needlwork looks at the evidence across multiple periods before deciding how much credit a channel has actually earned.
Spending more does not always produce proportionally more revenue.
Example: Google Non-Brand Ads
What this means
Result: You see where you're overspending, not underspending.
Why it matters
Helps you invest the right amount in the right channels to maximize growth and profitability.
Different metrics. One scale. Always comparable.
Normalization
Metrics like revenue, ROAS, and search volume all use different units. Needlwork converts them onto the same scale so they can be compared fairly.
Extreme values
One unusually good or unusually bad month should not dominate the overall score.
Trends
Needlwork looks for consistent movement over time instead of reacting to a single month.
Confidence
Confidence reflects how complete and reliable your uploaded data is.
Why it matters
Fair, stable, and comparable scores that show the real health of your marketing.
You don’t just know whether you’re improving. You know whether you’re ahead or behind comparable brands.
A trend line only tells you about your own history. Benchmarking adds the missing half of the picture: how that same performance compares to other brands in your category.
Why historical trends alone aren’t enough
Growing 15% a year sounds strong until you learn your category is typically growing 25%. Historical trends can tell you whether you’re moving in the right direction, but on their own they can’t tell you whether that pace is actually good.
How Needlwork combines the two
Where a category benchmark exists, Needlwork compares your metric against the industry median and gives you a plain-language standing, for example "Above Median" or "Near Median", instead of just a raw number. That standing sits alongside your own trend, so a score always carries both dimensions: is it moving, and is it competitive.
How this adds context to scores and recommendations
A pillar score already reflects your own trend, but the benchmark badge next to it tells you whether that trend is enough to keep pace with your category. Recommendations use the same context: a channel that looks fine on its own trend line can still be prioritized differently once you know how its underlying metric compares to the category.
Why a good-looking metric can still be average
A repeat purchase rate of 30% looks solid in isolation. If your category’s median is 35%, that same number is actually below average. Benchmarking exists specifically to catch this: a metric that looks good on its own can be perfectly ordinary once you see where the category actually sits.
What’s benchmarked today
Benchmarked today
Not benchmarked yet
These three are scored against your own history instead, since no reliable cross-brand benchmark exists for them yet.
Standings are always qualitative, for example "Above Median" or "Near Median", never a specific percentile rank. Needlwork doesn’t claim more precision than the underlying data supports.
We combine multiple signals to recommend where to act next.
Multiple Signals
We look at spend, returns, trends, efficiency, demand, seasonality, and more.
Identify Opportunities
We find areas with the biggest potential for improvement.
Estimate Impact
We estimate the possible impact and effort required.
Prioritize
We rank opportunities based on impact, confidence, and effort.
Why trust it?
Recommendations are based on data, not guesswork, but you’re always in control of the final decision.
Ready to see it in action?
Open a real Brief, built from real data, and see how Needlwork reasons about a brand like yours.
Or use the button at the top to skip ahead
Your data is never used for model training or shared with anyone.