Weekly report
The manager receives a summary of the changes without manually compiling the tables.
Processes · AYSiTE automation
AI sales and advertising analytics
We combine data from various sources and turn numbers into answers: what has changed, why and where to look first.
A single dashboard of key indicatorsAutomatic reports on scheduleDetection of anomalies and weak stages
The result
what are you will receive
Identify problems faster and make decisions based on data, not gut feeling.
- A single dashboard of key indicators
- Automatic reports on schedule
- Detection of anomalies and weak stages
- Explanations and hypotheses to test
Examples
How it works in practice
Anomaly
The system notices a sharp drop in conversion and shows where it started.
Segments
You can see which customers, products and channels give the best result.
How we work
Method of work
How do we bring the scattered data into one screen and explain the changes
Data audit
What is going together correctly and what is not.
Sources
Advertising, CRM, sales and expenses in one model.
Indicators
We choose those that make decisions.
Dashboard
One screen instead of five offices.
AI explanation
What grew, what fell and where to look first.
Notification
Sharp deviations come by themselves, without manual checks.
FAQ
Frequently asked questions
What is usually asked before starting: ai-analytics.
No. He finds patterns and prepares explanations, and the business decision remains with the responsible person.
CRM, advertising cabinets, site analytics, tables and other systems with API or export.
You can start without a technical task
Describe what takes time.
We will offer the scheme.
Reviews
Reviews clients
★★★★★
Cheers, honest feedback for potential customers. I have worked with many people, but no one had such communication as here (requests were processed very quickly, creative ideas, speed, quick solutions to problems, everything at the highest level) If you are choosing people to create a website or something similar, you are in the right place. I wish you development and prosperity.
RomanCleaning company Goldi Clean
★★★★★
We are sincerely satisfied with all the work done and communication. All our wishes regarding the site were fulfilled and everything was said. Thank you🩷
DianaNEC "Harmony"
★★★★★
Thank you, I am very satisfied.
SvetlanaBeauty studio of Svitlana Mazur
AI sales and advertising analytics: in detail
Analytics are not needed for reports, but for decisions. The problem of most businesses is not the lack of data, but the fact that it is scattered: advertising in one office, applications in CRM, sales in a table, expenses in accounting.
As long as no one confuses them, decisions are made by gut feeling, and the loudest channel wins the most effective. We collect data into one dashboard and add an AI layer that explains the changes in words: what went up, what went down, what are the most likely causes, what to look at first.
The goal is not beautiful schedules, but a short list of actions for the week. If after opening the dashboard it is not clear what to do, the dashboard is not made correctly.
What we reduce to one screen
Requests by source and period, cost per request, conversion by funnel stage, response rate, average check, repeat purchases, team downloads.
The set of indicators is always selected for the business — a universal dashboard is usually not read by anyone. For a service business, the workload of hours is critical, for a store - customer return, for B2B - the length of the transaction cycle.
- One dashboard instead of five cabinets.
- Indicators for your model, not templated.
- Explanation of changes in plain language.
- Notification of sharp deviations.
What exactly does AI do?
Finds anomalies and describes them: "ad requests are down 30% since Tuesday, while cost per call is up" - and tells you which slices to check.
Prepares short summaries for the week and month. It is not a replacement for analytics, but the first filter that saves hours of looking at charts and prevents you from missing a downturn when it can still be corrected.
Where to start if there is almost no data
From basic: correct accounting of applications with source and date. This is one step, after which it makes sense to calculate everything else.
Building complex analytics on incomplete data is a guaranteed path to wrong conclusions: the system will confidently show that "Instagram is not working", although half of the calls from there were simply not marked.
Typical errors in numbers
Count applications instead of deals. Compare months without taking into account the season. Look at the average check without breakdown by services. Evaluate the channel based on the last click, ignoring where the person first came from.
We talk about these pitfalls at the setup stage, because they are the ones that most often lead to the disabling of working ads.
Who needs it
Businesses with an advertising budget, several contact channels and a sales team.
If there are several applications per week and all of them go through one person, a simple table is enough, and we will say it directly, and not sell a dashboard for the sake of a dashboard.