AI campaign insights: a reading, not just a chart
A campaign dashboard shows how many messages were delivered, read and answered — but it rarely says what to do with that number. After a bulk send campaign runs, SDRBOT.ai uses AI to read that data and write a summary in plain language: what worked, what did not work, a performance score and specific recommendations for the next campaign, compared against your own history.
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Beyond the dashboard, a written reading
The campaign dashboard already shows the delivery, read and reply funnel in charts — that is pure metrics, with no AI involved. What the AI adds is a separate layer: a written executive summary, a performance score from 0 to 100 and a list of categorized points of attention, each with a practical recommendation attached.
Every point of attention it identifies arrives already classified by type and by priority, so whoever looks at the result knows immediately what deserves attention now and what is only a fine adjustment for the next round of sending.
That analysis looks at data beyond the obvious delivery and read numbers: engagement distribution by hour of the day, average response time and the performance of each variant, if the campaign ran an A/B test — information almost nobody would cross-reference by hand campaign after campaign.
Compared against your own history, not a generic benchmark
The analysis does not look at the campaign in isolation: it pulls your organization's most recent completed campaigns and compares the current result against that recent history, alongside general market references for the WhatsApp channel. That helps answer a more useful question than "was this campaign good?" — namely "was this campaign better or worse than your last ones?".
When the campaign includes an A/B test, the comparison between variants enters the analysis too, with the AI pointing out which one performed better and, where possible, a hypothesis for why — it is not the AI running the test, it is the AI reading the result the test already produced.
A recommendation for next time, not just a diagnosis
Every point of attention the AI identifies comes with a practical recommendation attached, prioritized by relevance, plus a separate list of best practices and tips specific to the next campaign you are about to send. The idea is to close the loop: analyze what already happened in order to improve what has yet to happen, instead of just filing the report away.
That result is cached for up to seven days after being generated, to avoid reprocessing the same campaign over and over without need, and it is recalculated automatically as soon as there is enough new data to change the reading. That window exists to balance two interests: keeping the reading reasonably fresh without forcing the system to reprocess the same campaign every time someone reopens the results screen on the same day.
It needs a minimum volume to work well
The AI analysis is only generated once the campaign has at least 10 messages sent — below that floor, the result tends to be statistically unreliable, and the screen shows only the standard dashboard metrics, with no AI summary. It is a deliberate limitation, so as not to hand back a generic reading built on thin data.
Below that floor of 10 sends, the system simply does not attempt the analysis — rather than returning an AI summary built on a sample too small to support any conclusion about timing, replies or a winning variant.
That means very small test campaigns, or sends to a short list, produce no AI insight — the feature was designed for campaigns with real volume, where patterns of timing, reply and variant actually show up in the numbers.
What changes for your team
- A summary in plain languageNot just numbers — text explaining what the numbers mean.
- Performance scoreA score from 0 to 100 for comparing campaigns quickly.
- Compared to your historyIt uses your last campaigns as the reference, not a generic benchmark.
- Practical recommendationSpecific tips for the next campaign, not just a diagnosis of the past.
Frequently asked questions
Does the AI analyze any campaign, even a small one?
No. The campaign needs at least 10 messages sent for the analysis to be generated — below that floor, the screen shows only the standard dashboard metrics, with no AI summary, because the result would be unreliable on so little data.
Does the analysis compare my campaign against any reference?
Yes, against two points of comparison: your most recent completed campaigns and general market references for the WhatsApp channel — which helps you tell whether the current result is improving or slipping relative to your own history.
Does the AI analyze A/B tests too?
Yes, when the campaign ran an A/B test the comparison between variants enters the analysis, with the AI pointing out which one performed better. The AI reads the result of the test — it does not decide or run the test itself.
Do I have to request the analysis every time I want to see it?
Not necessarily. The result is cached for up to seven days after being generated, to avoid reprocessing the same campaign without need, and it is recalculated automatically when there is enough new data to change the reading.
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