An AI agent that runs your campaigns

Connect your ad accounts and CRM — the agent analyzes channels, drafts content and creatives, tracks ROI, and sends the report.

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Выручка по каналам · июнь
обновлено сегодня

What the agent takes on

One agent runs the whole cycle — from pulling the data to a finished report. Switch tabs to see how.

Channel analytics on autopilot

Pulls ad platforms, marketplaces, and CRM into one report: CPL, ROMI, and revenue by every source.

Отчёт по Директу и VK Ads
Перерасход бюджета → стоп-сигнал
Контент-план на неделю
Сводка упоминаний бренда

Everything a marketer needs — in one agent

From analytics to product listings. The agent takes the routine so you can focus on strategy.

End-to-end analytics

Brings Yandex Direct, VK Ads, marketplaces and CRM into one report with CPL and ROMI per source.

Content & copywriting

Posts, newsletters, descriptions and headlines in your brand voice — in batches, tuned to each segment.

Listings & creatives

Product descriptions, SEO and banners for marketplaces and social — ready to publish.

Email & chat campaigns

Email and messenger sequences — from abandoned carts to re-engaging your base.

Competitor monitoring

Tracks rivals' prices, promos and content and sends a summary whenever something changes.

Reports for leadership

Campaign results with conclusions and recommendations — a ready dashboard or email, no manual work.

Marketplaces

Promotion, bids and sales analytics on Wildberries and Ozon — in one place with your ads.

Scheduled tasks

Builds reports and checks channels on a schedule — every morning, no reminders.

Your marketing stack — already connected

All integrations

Direct, VK Ads, Metrica, marketplaces and messengers connect in minutes. Your data stays in your systems.

Яндекс Директ
VK Реклама
Яндекс Метрика
Wordstat
Wildberries
Ozon
Telegram
Instagram
Unisender

What you can hand off — in one message

Describe the task in plain words — the agent gathers the data, formats the result and sends it to you.
Build a report on ad channels for [period — week from … to …] using data from Yandex Direct, VK Ads and Metrica. For each channel and campaign: spend, clicks, conversions on goal [goal name in Metrica], revenue from that goal, ROMI and the change versus [the previous week]. Calculate ROMI only where revenue comes from Metrica. Where there is no revenue — don't substitute an average order value and don't carry it over from another channel, move such channels into a "ROMI not calculated" block and write what is missing. Don't explain a drop by seasonality until you show the same week a year ago. Output XLSX: a sheet by channels, a sheet by campaigns and five lines of conclusions — what grew, what fell and where to move budget.
Write [5] post variants for the launch of [product and what changes in it] for [Telegram / VK]. Audience: [who they are, what they already know about us, what stops them]. Offer and deadline: [what we offer]. Make the angles different: usefulness, a specific pain, "before and after", handling an objection, news. Rely only on the facts I gave. Don't invent numbers, deadlines, testimonials or client names: if a fact is missing for a strong line — leave a [gap] and write what to fill in. Take the tone from the attached posts, not from ad templates. Output for each variant: the angle in one word, text within the platform limit, a call to action and a line "who it's aimed at".
Find where in Yandex Direct spend over [period] produced no result on goal [goal name]. Go down the levels: campaign, ad group, ad, search phrase and ad network placement. Include in the report only rows with spend above [threshold] — don't draw conclusions on smaller samples, collect them in a separate "not enough data" line. Don't call a row wasted spend if it has conversions that are simply expensive: separate "no conversions at all" from "cost above target" — those are different decisions. Separately show phrases with high CTR and zero conversions, and ad network placements with a bounce rate above [80%]. Output a table: level, name, spend, clicks, conversions, what you suggest doing (pause / add as negative / lower the bid) and how much money that frees up over [period].
Write a chain of three abandoned-cart emails: [how many hours until the first], [the second], [the third]. Make the mechanics different: the first — a reminder and removing a technical barrier, the second — an answer to the reason for hesitation [delivery / price / size choice], the third — a deadline [what exactly is limited]. Write only about what I listed. Don't invent discounts, free delivery, "only 2 left", testimonials and ratings: if a mechanic requires such a block — put [filled in from data] and describe where the value comes from. For each email: three subject line variants and a preheader, the text, one button with its label, the send time and the condition under which the email doesn't go out (order paid, item out of stock).
Compare prices for my items on Wildberries with competitors using MPStats data as of [snapshot date]. My SKU list: [article numbers or category]. Treat a competitor as comparable only on a match of [category, volume/size, composition, brand segment]. Don't compare different pack sizes and bundles with single items — move such pairs into "not comparable" and explain how they differ. For each SKU show: my price before and after discount, the median and the price range of competitors, the difference in percent, my stock and competitors' stock, the search position for [key query]. Flag items where I'm above the median by more than [10%] while orders are falling, and where I'm the lowest of all but sales aren't growing. Output a table by SKU and a short list: where the price is worth revisiting and in which direction.
Rewrite the listings [article numbers] on [Ozon / Wildberries]: title, specifications and description. Take buyer queries for this category and distribute them across the fields: the main ones — into the title and the first specifications, the rest — into the description, without listing them comma-separated. Write only from the specifications in the listing and from what I attached. Don't add composition, country of origin, warranty, certificates or product properties: if a field is empty, put [to clarify] and move it into the list of missing data. Respect the platform's field limits and don't repeat a single keyword more than [3] times. Output for each article number: the title, a specifications table, the description text, the list of queries used and the list of fields I have to fill in myself.
Link spend in Yandex Direct with leads in Bitrix24 for [period] via [source field / utm], reconcile conversions against Metrica. For each channel and campaign calculate: spend, number of leads in CRM, CPL, number of leads in statuses [qualified] and the cost of a qualified lead. Separately show quality: duplicates, spam and rejections with reason [not relevant], the share of leads left untouched for longer than [N hours]. Don't distribute leads without a source across channels proportionally — keep them as a separate line "source not identified" with their share of the total. Show the discrepancy between conversions in Metrica and leads in CRM as a number, don't smooth it over. Don't include revenue and deals in this report. Output a table by channels, a table by campaigns and three lines: where CPL grew, where quality fell at the same CPL, where leads aren't being worked.
Analyze the finished campaign [name, dates] in Direct and Metrica and propose [5] hypotheses for the next launch. Goal of the next launch: [what matters more — volume or cost]. Look where the potential sits: segments with good conversion and small reach, creatives with high CTR and a weak landing page, times and geographies with different cost per goal, devices, steps on the landing page where people drop off. Frame each hypothesis like this: what we change, which numbers from this campaign it's built on, the expected effect as a range, how we'll test it and on what budget. Don't pass off as a finding something explained by random spread on a small sample, and don't fit the explanation to a decision already made — if there isn't enough data for a conclusion, call it an idea for a test, not a hypothesis.
Calculate the economics of a [discount size] promo on [article number / product] on [Ozon / Wildberries] for [period]. Take the current price and the platform commission, cost from 1C, logistics, storage, acquiring and [ad cost share] for this product. Calculate margin per unit now and with the discount, the break-even sales uplift in units and percent, and profit in three scenarios: sales [+X%], [+Y%], [+Z%]. If I didn't specify some cost item — don't take a market average, put it as a "not accounted for" line and show how it moves the result. Separately calculate the cannibalisation effect: how many sales will shift from [adjacent article numbers] and what that means for profit across the group. Output a scenario table, the loss point and one line: at what uplift the promo makes sense.
Collect [10] topics for a content plan for [month] for [Telegram / VK]. First look at my publications over [period]: which formats and angles got above-average response, which topics repeated without result. Describe this in two or three lines before the topic list. Goals for the month: [warm-up / sales / audience growth] and events: [launch, season, date]. Each topic: format, angle, who it's for, which goal it leads to and which facts it's built on. Take facts only from my materials. Don't make up cases, result figures and client quotes: where an example is needed — put [case needed] and describe which one exactly. Don't propose a topic if it already ran on my channel within [period] — or say how the new angle differs. Output a table of topics and a week-by-week layout.

FAQ

Where data is stored and how access is protected — covered separately: security overview

It connects via API to Russian ad platforms, marketplaces (Wildberries, Ozon, Yandex Market), Bitrix24, and amoCRM. Data from every channel is consolidated into a single report.

By default it prepares drafts for your approval. Grant publishing rights for specific channels and posts and newsletters go out on schedule with no input from you.

No. Describe the task in plain language and the agent figures out the data and formats on its own. You don't need a developer or a separate analyst on staff.

Upload your guidelines, past posts, and examples — the agent learns the style and holds it across every asset. The more examples, the sharper the voice.

Ready-made use cases

All use cases
A weekly all-channel report with ROMI and conclusions

On Monday you have to say which channel brought money, not just which one spent it. The agent pulls spend and revenue per channel for the week.

Write launch post variants tuned to your audience

The launch is in three days and the copy starts from a blank page again. You get five genuinely different angles, sized for Telegram and VK.

Find Yandex Direct campaigns that burn budget

Spend is on plan but the leads aren't. The agent finds campaigns and search phrases that spent money without a single target action, and totals the saving.

Create an abandoned-cart email sequence

The cart is abandoned and all that follows is one "you forgot an item" email. You get three emails with different arguments, subject lines and timing.

Compare your Wildberries prices with competitors

Sales on an item dropped and nobody can say whether price is the reason. The agent matches your items to real analogues and shows where you left the band.

Write descriptions and SEO for product cards

Descriptions were copied from the supplier and the listing never shows up in search. The agent rebuilds the title, attributes and copy around real queries.

A leads and cost-per-lead (CPL) dashboard for the stand-up

The ad account shows more leads than the CRM and nobody explains the gap. The agent links spend to deals in Bitrix24 and works out cost per lead.

Find growth opportunities in your last campaign

The campaign is over, the totals are in, and the next move is argued on gut feel. You get five hypotheses, each tied to the number it stands on.

Calculate the economics of a promo on your flagship

The platform is inviting you into a promo and the answer is due Friday. The agent works out how much you must sell at the discount to keep profit level.

Collect ideas for a monthly content plan

The plan gets assembled on the 30th and half the topics come off the top of someone's head. You get ten grounded in posts people actually read.

Guides on this topic

Marketing that never hits pause

Connect your channels in minutes and hand campaigns, content, and analytics to the agent — so your team can focus on strategy.

Try for free