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LDOO is conversational analytics for agencies and marketing teams.
Answer #50 is better than answer #1.
Most analytics tools forget everything between sessions. LDOO accumulates context — 90-day baselines, conversation history, client goals, report insights, feedback corrections. Every answer is informed by everything that came before it. The AI doesn't just know the numbers. It knows what's normal, what changed, and what you care about.
Six layers of context in every answer.
Each layer is injected into the AI prompt automatically. You don't configure any of this — it builds over time as you use LDOO.
90-day baselines
Statistical normals computed from the last 90 days of data for each client, source, and metric. When LDOO says "CPA is above normal," it means it — the baseline is calculated, not guessed.
Conversation history
Key findings from your last 30 days of conversations about each client. LDOO references prior analysis instead of starting from scratch every time.
Client goals & KPIs
Industry, primary KPI, targets, seasonality notes. When LDOO says "ROAS is within your target," it's checking against goals you set — not making a generic judgment.
Report memories
After every report is generated, LDOO distills the narrative and recommendations into topic-tagged memories. Future answers reference these — efficiency, channel focus, known issues.
Active alerts
Unread anomaly alerts are injected into the prompt so LDOO can proactively surface them. "CPA spiked on Tuesday" appears in the answer before you ask about it.
Feedback patterns
When you give thumbs-down on an answer, the pattern is recorded. Future answers for that client avoid the same mistake. Quality improves with use.
Computed, not configured.
After every data sync, LDOO recomputes 90-day statistical normals for each client, source, and metric. This is what powers the difference between “CPA is $65” and “CPA is $65 — above your normal $40-$55 range and the highest in three months.”
Without context vs with context.
This is the same question asked of the same data. The difference is whether the AI has accumulated context about the client.
“CPA this week is $65. This is higher than last week's $44. Consider reviewing your campaigns and adjusting bids to reduce costs.”
“CPA is $65 — above your normal $40-$55 range and the highest in three months. The spike is concentrated in the Retargeting campaign where frequency hit 6.2. Last time this happened (Feb 12), refreshing creative brought CPA back to $42 within a week. Your target is $50, so this needs action.”
Always on. Zero configuration.
Statistical normals recomputed after every sync. 90-day window. Per client, per source, per metric.
Key findings from the last 30 days of conversations are injected into every answer. Prior analysis compounds.
Narratives and recommendations from generated reports are distilled into reusable memories by topic.
"Remembering N prior conversations" badge on every answer card. You always know what context the AI is using.
The AI that knows
your clients.
Every question you ask makes the next answer better. Baselines, goals, history, feedback — context accumulates automatically.