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    Social Media

    Facebook Ads Case Study:

    Generated ₹ 7.6 Crore Revenue For One of Our Client
    Duration – 6 April 2019 – 18 March 2020
    Ecommerce Industry – Apparel

    ✅ Website Purchase – 74890
    ✅ Amount Spent –₹ 13,111,676.75
    ✅ Website Conversion Value – ₹ 76,164,875.00
    ✅ ROAS – 5.81
    ✅ Maximum Sale a Day – 647
    ✅ Maximum Spent a Day – ₹ 97546.00
    ✅ Maximum WCV – ₹ 783458.00

    Campaign Details
    • No of campaigns – 47
    • Like -1
    • Traffic -3
    • Conversion – 33
    • Catalogue Sales – 10
    • No. Ad Set – 150
    • No of Ads – 500

    We created the customer persona based on Client’s inputs. We kept updating the customer journey through cohorts in Facebook and Google Analytics.

    👉Tools and Analytics Used:

    • Behavioral Analytics: Hotjar,
    • Web Analytics: Google Analytics, Facebook Analytics, GTM
    • Competitor Analysis-Advertsuite
    • Customer Persona –Uexpressia
    • Funnel Analytics: Geru
    • Internal Tools for Reporting Formats

    👉Funnel Structure on Facebook:

    TOF:
    • Traffic Campaign-Interests
    • Video Reach-Interests
    • Conversion Campaign-LLA, LLA Value Pixel Audience, LLA from Catalogue Source
    • Catalogue Sales

    MOF: Engaged Page Audience and Video watched (More than 50%)

    BOF: We used refined retargeting audience through Google Tag Manager. Used Sequential retargeting and Catalogue ads for dynamic retargeting.

    Super BOF: We call targeting to existing customers as Super BOF. It performed well as we cross targeted various best-sellers across categories.

    Google Remarketing: We used display ads for aggressive BOF campaigns.

    Creative: Single Image, carousal, instant experience, videos. Video length up to 12 seconds. Used different formats for Instagram stories and News Feed.

    Funnel Analytics: We kept check the following metrics across funnels stages: i.e.- TOF, MOF and BOF.
    • CTR
    • CPM
    • Frequency
    • ATC
    • Cost per ATC
    • ICT
    • Cost per ICT
    • Cost Per Acquisition (CPA)
    • No of purchases
    • ROAS
    • Unique Link Clicks/No of Landing Page
    • AOV
    • Audience Saturation and Overlap

    👉Highlights:
    • Used CBO & ABO
    • Used automated rules for monitoring and scaling.
    • Tested a lot of ad copies, creative and videos to find a winner.
    • A/B testing in first two weeks
    • Used Facebook Analytics for optimization.
    • Funnel Analytics
    • 40% Manual Bidding in campaigns.

    RTO – 20-27%
    COD – 80%
    PRE PAID – 20%

    👉Team involved – 5
    • Campaign manager -2
    • Creative designer -1
    • Data Analyzers -1
    • Ads Copywriter – 1