• aMEHzon
  • Posts
  • Mastering New-to-Brand Analysis: Your Secret Weapon for Customer Acquisition

Mastering New-to-Brand Analysis: Your Secret Weapon for Customer Acquisition

Why Your Amazon Strategy Might Be Leaving Money on the Table

Author

Nick Padilla
November 11, 2024

Picture this: You're running Amazon campaigns, getting decent sales, but something's missing. What if I told you that hidden in your data is the key to unlocking a flood of new customers? That's where New-to-Brand (NTB) analysis comes in – your secret weapon for turning casual browsers into first-time buyers.

What You're About to Learn

  1. How to identify your most effective ASINs for acquiring new customers

  2. The exact metrics that matter (and why)

  3. Step-by-step analysis techniques that will make you look like a data genius

  4. Actionable strategies to optimize your campaigns for new customer acquisition

Let's turn that data into dollars, shall we?

The Foundation: Understanding New-to-Brand Analytics 🎯

What Actually Counts as "New-to-Brand"?

  • A customer who hasn't bought from your brand in the last 365 days

  • Purchase must be ad-attributed on Amazon

  • Must have occurred within the 14-day attribution window

Pro Tip: Always wait two weeks after your campaign ends before running your analysis. Those late-blooming conversions matter!

The Metrics That Actually Matter 📊

Your New Customer Arsenal:

  1. All Users with Purchase

    • Total number of customers who bought your product

    • Your baseline for measuring success

  2. NTB Users

    • Number of first-time customers

    • Your growth indicator

  3. NTB Percentage

    • Percentage of new vs. total customers

    • Your efficiency metric

  4. Gateway ASIN Rank

    • How your products stack up against each other

    • Your strategic planning tool

Strategy Deep Dive: Making the Numbers Work for You 🚀

1. Identify Your Gateway Champions

Look for ASINs that are:

  • Bringing in the highest volume of new customers

  • Converting at above-average NTB rates

  • Consistently performing over time

Real-World Example:

Top Performer: ASIN2345 - 72.33% NTB percentage (vs. 56.11% average) - 1.29x more likely to attract new customers - Perfect for new customer acquisition campaigns

2. Optimize for Customer Types

For New Customer Acquisition:

  • Focus on ASINs with high NTB percentages (60%+)

  • Test variations of your top-performing NTB ASINs

  • Allocate higher budgets to proven gateway products

For Customer Retention:

  • Target ASINs with lower NTB rates (like ASIN5678 at 48.69%)

  • Perfect for remarketing campaigns

  • Focus on cross-selling and upselling opportunities

3. Campaign Structure Strategy

New Customer Campaigns:

  1. Isolate high NTB percentage ASINs

  2. Create dedicated campaigns

  3. Optimize bidding for first-time purchases

  4. Test different ad formats

Retention Campaigns:

  1. Group low NTB percentage ASINs

  2. Focus on repeat customer targeting

  3. Emphasize brand loyalty benefits

  4. Test bundle offers

Deep Dive: The Power of Query Analysis 🔍

Query 1: The Exploratory Query

-- Exploratory Query: Exploratory Query for NTB Gateway ASINs --
-- Identify campaigns and campaign_ids.
SELECT
  campaign,
  CONCAT('campaign_id: ', campaign_id_string) AS campaign_id,
  CASE
    WHEN ad_product_type IS NULL THEN 'DSP'
    ELSE ad_product_type
  END AS ad_product_type,
  SUM(purchases) AS purchases
FROM
  amazon_attributed_events_by_conversion_time
WHERE
  (
    CUSTOM_PARAMETER('ad_product_type') IS NULL
    OR CARDINALITY(CUSTOM_PARAMETER('ad_product_type')) = 0
    OR ARRAY_CONTAINS(
      CUSTOM_PARAMETER('ad_product_type'),
      COALESCE(ad_product_type, 'DSP')
    )
  )
  AND (
    (CUSTOM_PARAMETER('tracked_asin') IS NULL)
    OR CARDINALITY(CUSTOM_PARAMETER('tracked_asin')) = 0
    OR ARRAY_CONTAINS(CUSTOM_PARAMETER('tracked_asin'), tracked_asin)
  )
GROUP BY
  1,
  2,
  3

Purpose: This is your reconnaissance mission. Before diving into detailed NTB analysis, this query helps you:

  1. Identify which campaigns exist in your data

  2. Get campaign IDs for filtering

  3. Understand your ad product mix

  4. See purchase volumes across campaigns

How to Use the Results:

  • Review the campaign list to decide which ones to include/exclude in your NTB analysis

  • Note campaign IDs for filtering in the main NTB query

  • Identify which ad product types are driving purchases

  • Use this information to make informed decisions about filtering in Query 2

Pro Tips:

  • Run this first to avoid missing important campaigns

  • Use the results to plan your filtering strategy

  • Pay attention to DSP vs. non-DSP performance differences

  • Look for campaigns that might skew your NTB analysis

Query 2: The NTB Gateway ASINs Query

-- Instructional Query: NTB Gateway ASINs --
WITH users AS (
  SELECT
    advertiser,
    tracked_asin,
    user_id,
    (IF(new_to_brand = TRUE, 1, 0)) AS ntb_users
  FROM
    amazon_attributed_events_by_conversion_time
  WHERE
    purchases > 0
    AND advertiser IS NOT NULL
    AND (
      CUSTOM_PARAMETER('campaign_id') IS NULL
      OR CARDINALITY(CUSTOM_PARAMETER('campaign_id')) = 0
      OR ARRAY_CONTAINS(
        CUSTOM_PARAMETER('campaign_id'),
        campaign_id_string
      )
    )
  GROUP BY
    advertiser,
    tracked_asin,
    user_id,
    new_to_brand
),
asin_ranks AS (
  SELECT
    advertiser,
    tracked_asin,
    COUNT(DISTINCT user_id) AS all_users_with_purchase,
    SUM(ntb_users) AS ntb_users,
    SUM(ntb_users) / COUNT(DISTINCT user_id) * 100 AS ntb_percentage
  FROM
    users
  GROUP BY
    advertiser,
    tracked_asin
)
SELECT
  advertiser,
  tracked_asin,
  all_users_with_purchase,
  ntb_users,
  ntb_percentage,
  RANK() OVER (
    PARTITION BY advertiser
    ORDER BY
      -- OPTIONAL UPDATE: if you want to rank by ntb_percentage instead of ntb_users, change ntb_users to ntb_percentage.
      ntb_users DESC
  ) AS gateway_asin_rank
FROM
  asin_ranks

Customization Options:

  1. Filter by Advertiser:

    WHERE advertiser SIMILAR TO 'xxxxxxxx'

    • Use this when focusing on specific brands

    • Replace 'xxxxxxxx' with your advertiser pattern

    • Great for multi-brand analyses

  2. Filter by Campaign:

    WHERE campaign in ('campaign_name1', 'campaign_name_2')

    • Use campaign names/IDs from Query 1

    • Perfect for analyzing specific campaign types

    • Helpful for seasonal or promotional analysis

  3. Modify Ranking Logic:

    RANK () OVER (PARTITION BY advertiser ORDER BY ntb_users DESC) as gateway_asin_rank.

    • Choose based on your primary KPI

    • Volume vs. efficiency trade-off

    • Different rankings tell different stories

Important Notes:

  • Without filters, query pulls all advertisers

  • ASINs are ranked separately for each advertiser

  • Rankings can be customized based on your KPIs

  • Always consider seasonal factors when interpreting results

Strategic Applications:

  1. Campaign Analysis:

    • Identify best-performing ASINs across campaigns

    • Compare performance across different ad types

    • Guide budget allocation decisions

  2. Product Strategy:

    • Find your true gateway products

    • Identify products better suited for retention

    • Guide new product development

  3. Customer Acquisition:

    • Optimize for new customer volume or efficiency

    • identify products with highest NTB potential

    • Guide promotional strategy

Making the Most of Both Queries

Step 1: Campaign Overview

  1. Run Query 1 to understand your campaign landscape

  2. Note top-performing campaign types

  3. Identify any underutilized ad products

Step 2: Deep Dive Analysis

  1. Run Query 2 to analyze NTB performance

  2. Cross-reference with Query 1 results

  3. Look for patterns in successful campaigns

Step 3: Strategic Implementation

  1. Adjust campaign structure based on findings

  2. Reallocate budget to high-performing areas

  3. Create new campaigns based on successful patterns

  4. Monitor and iterate monthly

Your Action Plan: Next Steps to Implementation 🎬

Today:

  1. Run the exploratory query to understand your campaign landscape

  2. Identify your top 10 ASINs by NTB users

  3. Calculate your baseline NTB percentage

This Week:

  1. Segment your ASINs into:

    • New customer acquisition champions (>60% NTB)

    • Retention products (<50% NTB)

    • Mixed performers (50-60% NTB)

  2. Begin restructuring campaigns based on NTB performance

This Month:

  1. Create dedicated new customer acquisition campaigns

  2. Test variations of your top NTB ASINs

  3. Monitor and adjust based on performance

Pro Tips for Power Users 💡

Analysis Best Practices:

  1. Always wait 14 days for complete data

  2. Consider seasonal variations in NTB rates

  3. Look for patterns in product categories

  4. Test both volume and percentage-based optimization

  5. Compare performance across different time periods

  6. Account for promotional calendar impacts

The Million-Dollar Questions Answered 🤔

Q: "How often should I run this analysis?" A: Monthly for active campaigns, quarterly for strategic planning.

Q: "What's a good NTB percentage?" A: Industry varies, but aim for 60%+ for acquisition-focused ASINs.

Q: "Should I stop promoting low NTB ASINs?" A: No! Repurpose them for retention campaigns.

Bottom Line: Your Success Metrics ✅

Track these weekly:

  • Overall NTB percentage trend

  • Top 3 NTB ASINs performance

  • Campaign ROI by NTB segment

  • New vs. repeat customer revenue

Remember: In the world of Amazon advertising, data isn't just numbers – it's your roadmap to growth. Now go forth and conquer those new customers!

P.S. If this analysis helped you find your gateway ASINs, just wait until you see what happens when you actually optimize for them. Your competition won't know what hit them.

Reply

or to participate.