DeepContext Playbook: Contextual Targeting That Scales

Quick answer

Use this five-step playbook to set up Eskimi DeepContext, prove impact, and scale contextual targeting fast. You get a Brand Blueprint, a Relevance Engine QA checklist, a placement audit CSV sample, and a 30-day scorecard you can run right away.

Why this matters

Keywords alone miss tone, intent, and cultural cues. Eskimi DeepContext reads full pages, detects tone and sentiment, and matches placements to a brand s goals in real time. That means fewer false brand-safety blocks, better relevance across languages, and faster activation.

What you can expect

• Fewer false positives when enforcing brand safety.
• Better ad relevance across 20+ markets.
• Real-time inventory signals you can act on.
• Transparent placement reasoning to audit and unblock good inventory.

Playbook overview: 5 steps

1. Define a Brand Blueprint.
2. Connect the Relevance Engine and QA it.
3. Run a placement audit and fix rules.
4. Run a 30-day scorecard experiment.
5. Scale with guardrails and multilingual checks.

Step 1: Build a Brand Blueprint

The Brand Blueprint tells the Relevance Engine what your brand wants and what to avoid. Keep it simple. Start with three must-have attributes and three avoid attributes.

Blueprint template (example)

• Must-have: Positive tone, travel lifestyle, family-friendly images.
• Must-have: Product intent (search or reviews for product category).
• Must-have: Local cultural keywords or phrases per market.
• Avoid: Hate speech, graphic violence, illegal activity.
• Avoid: Competitor comparison pages with negative sentiment.
• Avoid: Misinformation and sensationalized medical claims.

Save this as a spreadsheet and upload it when you set up DeepContext. You will edit it during the pilot based on placement feedback.

Step 2: Connect and QA the Relevance Engine

The Relevance Engine scans live content and scores pages against your Brand Blueprint. Do these checks before you run live traffic.

Simple QA checklist

• Confirm language coverage for each market. DeepContext supports many languages; test in the top 3 markets first.
• Pull 100 sampled pages the engine selected. Audit for tone, intent, and sensitivity.
• Check explanation logs so you can see why each placement was chosen.
• Adjust blueprint rules that are too broad or too strict.

Use the platform s feedback loop to tweak rules. The system should show transparent placement reasons so you can unblock good inventory instead of blocking whole sites.

Step 3: Run a placement audit (and a CSV sample)

Export placements to review what actually served. Look for false brand-safety blocks and missed opportunities. Use this small CSV shape to standardize audits.

site_url, page_url, detected_language, relevance_score, reason_tags, action_recommendation
example.com, https://example.com/article1, en, 0.92, "positive_tone;travel;review", allow
example.jp, https://example.jp/post2, ja, 0.45, "neutral_tone;mention_competitor", review
news.example, https://news.example/story3, es, 0.10, "graphic;violence", block

Export a full CSV from the platform and add a column for your action. Pick "allow" for high relevance and safe pages, "review" for borderline cases, and "block" for clear violations.

Step 4: 30-day scorecard experiment

Run a controlled pilot for 30 days. Split traffic between your current contextual or keyword approach and DeepContext. Measure these KPIs:

• Context-aligned impressions (percentage of impressions matching Brand Blueprint).
• False brand-safety blocks (pages blocked wrongly).
• View-through rate and CTR by placement type.
• CPM and conversion lift where applicable.

How to run the scorecard

1. Week 0: Baseline current contextual performance for two weeks.
2. Days 1 -7: Launch DeepContext with conservative rules. Collect placements and explanations.
3. Days 8 -21: Iterate the Blueprint using audit CSV inputs.
4. Days 22 -30: Run optimized rules and compare to baseline.

Goal: reduce false brand-safety blocks and increase context-aligned impressions within 30 days. Use the platform s real-time insights to accelerate changes. See DeepContext product notes for how real-time scanning works.

Step 5: Scale with guardrails

Once the pilot shows wins, scale across markets. Keep these guardrails in place.

• Market-specific Blueprints. Small cultural changes matter across regions.
• Automated "review" queue for borderline pages so humans decide quickly.
• Weekly placement reports with a focus on trending topics and new inventory.
• Brand-safety thresholds that trade off scale for control during big live events.

Mini case examples

Use these short examples as patterns you can copy.

• Global brand: Created per-country Blueprints. Result: 12% lift in context-aligned impressions and 30% fewer false blocks in three markets.
• Agency: Replaced keyword rules with DeepContext for APAC buys. Result: less audience loss and better multilingual matches.
• Publisher: Showed brand-safe contextual placements to clients. Result: higher CPMs on premium inventory.

Quick tips and traps to avoid

• Tip: Start conservative, then expand. Don t open the gates on day 1.
• Tip: Use the platform s explanation logs to unblock good pages fast.
• Trap: Avoid one-size-fits-all Blueprints across languages. Local phrases change meaning.
• Trap: Don t treat relevance_score as binary. Review middling scores.

FAQ

Will DeepContext replace keywords?

No. It augments targeting. Use keywords for search intent and DeepContext for tone, sentiment, and cultural fit.

Can I review placements before they run?

Yes. The platform supports pre-bid checks and transparent placement reasons so you can audit and approve inventory.

How do I reduce false brand-safety blocks?

Audit the blocks, use the CSV sample to log false positives, and loosen Blueprint rules where the engine misclassified safe pages. The goal is manual unblock, not blanket site bans.

Next steps

1. Download a Blueprint template from the product page at Eskimi DeepContext.
2. Run the 30-day scorecard and export the placement CSV weekly.
3. Share results with brand-safety and media teams. Use the audit to expand safe inventory.

Resources

• Introducing DeepContext product blog with setup notes.
• MarTech360 coverage industry take on launch and multilingual support.
• Deep-Context overview company info and platform description.

Run this playbook, collect the data, and iterate. Start small, measure the lift, and scale with rules that match your brand s voice in every market.