Build Custom AI Agents to automate repetitive analysis, provide deep insights, and recommend ways to optimize your marketing campaigns based on data
Answering a “not-so-simple” question
The campaign manager logs into the dashboard.
The manager reviews multiple dashboards on various social media platforms, examining key metrics such as reach, engagement rates, and conversion rates to assess the effectiveness of ongoing campaigns.
Next, the manager shifts to audience insights, focusing on demographics, behavior trends, and content performance.
The manager analyzes return on investment metrics, including cost-per-click and conversion rates, to evaluate profitability and optimize budget allocation
Seeing something interesting, the campaign manager sends a Slack message to the data analyst.
The campaign manager creates a ticket in Jira.
The analyst manually writes SQL or Python code and returns the answer.
A second question is raised by the campaign manager to the data analyst, "The cycle repeats."
Now that the campaign manager has all of the information, they plan to move the budget from campaign A on Facebook, to campaign C on TikTok.
The campaign manager opens the Facebook ad manager, navigates the UI, and adjusts the budget as necessary.
The campaign manager now opens TikTok ads and adjusts the budget accordingly.
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The campaign Manager logs into Cimba and asks, “How can I optimize my marketing spend?” A workflow is automatically launched to analyze key metrics from all advertising spend sources with Cimba.
As Cimba summarizes its findings automatically, it presents the metrics to the user with visualizations and highlights.
Cimba recommends that the campaign manager move the budget from Campaign A on Facebook to Campaign C on TikTok. The campaign manager receives projections on these metrics from Cimba.
The campaign manager approves this action, and Cimba executes the appropriate task to make the change Campaign manager then opens TikTok ads and adjusts budgets accordingly.
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“How do I optimize my Marketing Spend?’’ Without Cimba AI
Campaign Manager Logs Into Dashboard Navigates multiple dashboards, viewing different insights to create a mental picture of how the campaigns are doing Sees something that is interesting, sends a slack message to a data analyst about it Data Analyst creates a ticket in Jira Data Analyst creates a ticket in Jira Data analyst manually writes SQL or Python code, returns answer (code disappears into the ether forever)Campaign Manager, seeing this, has another questionCycle repeats
Now that the campaign manager has all of the information, they plan to move budget from campaign A on Facebook, to campaign C on TikTok. Campaign manager opens facebook ad manager, navigates the UI, and adjusts the budget accordingly. Campaign manager opens TikTok ads, and adjusts the budget accordingly executes the appropriate task to make the change.
Metrics:
Time Spent: 11 Days
People Involved: 2
UIs Navigated: 6
“How do I optimize my Marketing Spend?’’ With Cimba AI
Campaign Manager Logs into CimbaAsks Cimba “how can I optimize my marketing spend?”Cimba automatically kicks off a workflow to anaylze key metrics from all advertising spend sources. Cimba returns these metrics to the user with visualizations and highlights. Cimba automatically summarizes its finding into a simple, easy to digest reportsCimba recommends actions to the campaign manager “you should move budget from Campaign A on Facebook to Campaign C on TikTok”.Campaign Manager asks Cimba “how would that impact my ROI, CPC, CTR, etc.”Cimba creates projections on these metrics and returns them to the campaign managerCampaign manager approves this action, and Cimba
Metrics:
Time Spent: 15 minutes
People Involved: 1
UIs Navigated: 1
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