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CASE STUDIES 

Case 1
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Case 1: A seamless campaign analytics system

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Introduction

  • One of the worlds leading retailer in electronics from North America approached us for help with Business Insights for their marketing campaigns.

  • They were gearing up for the holiday season was fast approaching and the they wanted to have a watertight strategy to meet their revenue goals during this critical season.

  • The client was already running multiple campaigns across all major channels and was spending big dollars on their marketing efforts.

The Challenge

  • The Holiday Season is one of the busiest times of the year for online retailers, generating a whopping one-fourth to one-third of their annual revenue in a matter of weeks. Considering the significant percentage of revenue that gets generated during this season, both brands and retailers plan exclusive budgets and promotions well ahead of time to capitalize on all the action happening through this festive time.
     

  • The challenge was to be able to make informed decisions from all the data generated. As there were too many things happening and too much data to look through, it was a herculean task to make sense of all the campaign performance data. They were literally looking for “a method to the madness”, a simple way to analysis and understand the impact of current and previously run campaigns, to be able strategically plan their campaign spends.

1Score Approach

  • How OneScore leader board was a perfect solution ?
    The “OneScore” leader board solution can be viewed as a simplified analytics tool that does away with the clutter of excessive data and clearly points out to what matters most. The pre-designed OneScore leader board was a perfect fit for the clients use case and it was an absolute hit with this client, as it simply helped rank and highlight the best performing campaigns and the team no longer had to spend hours trying to analysis multiple metrics to make decisions on marketing spend. The client admitted that we had solved one of their major pain points.
     

  • Adding Value
    OneScore team spent time to further understand the business, KPI’s important to the client at different levels and standard practices of the company to come up with a custom scoring mechanism based on the priority metrics. The leader board was designed in a way that it had an option to switch to a detail analysis page, where the marketing teams could deep dive and look at multiple metrics by other campaign attributes, without having to switch platforms.
     

  • The team also helped the client understand the impact a particular campaign had when run
    In order to do this, OneScore team decided to execute Lift Analysis, by which we were able to determine the incremental value of the targeted metrics from the campaign effort. This gave the client a lot of clarity on which campaign performed well in the past and helped them plan to execute strategies accordingly for the future.

Benefits

  • Simplified Analysis by OneScore leaderboard

  • Clarity on the impact of campaigns on key metrics

  • Clear Business Insights for Strategic Planning of campaign spends

Case 2
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Case 2: Problem-solving using custom attribution model

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Introduction

  • The client is a well-known and trusted home builder

  • They run multiple marketing campaigns across all channels

  • The business is facing major competition from other home builders

  • And the client was spending a lot of money on their marketing efforts, however
    was not able to attribute success to the campaigns and channels accurately

The Challenge

  • The client’s major source of revenue was through leads coming to the website. And marketing spends were being poured into multiple channels to drive maximum leads to the website.

  • The ask was to attribute real dollar value to these channels, they had established that the “last touch point” approach that they were following was not giving them accurate results.

  • The challenge was to find the real revenue associated with the leads from specific channels, to be able to make informed decision on spends and improve the Return on Investment.

1Score Approach

The immediate call to action was to fix the Attribution Model
 

  • We started by collecting the weekly data from all the channels

  • A data study was done to understand the relationship between these channels

  • After our study, we implemented Marketing mix as the chosen analysis model

  • Both bottom of the funnel and top of the funnel attribution was completed

  • Top of the funnel attribution was on the Website Leads and bottom funnel on Revenue

  • Finally our OneScore attribution dashboard was delivered along with comparison with heuristic models, the user could now just change a control and compare the numbers


Value addition through Spend Optimizer
 

During our engagement, the client was happy to explore the full potential of our OneScore attribution, we recommended the OneScore spend optimizer, as the spend optimizer makes use of the learnings from the attribution model and automatically suggests spend distribution. The spend distribution is suggested based on the desired values which are entered by the user. This was a huge advancement in the way the client was managing their marketing spends.

Benefits

  • Discovered the real value generating channels

  • Embraced a more accurate way of ROI calculation

  • Helped optimizing the marketing spend

  • Improved ROI

Case 3
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Case 3: Boosting up operational efficiency

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Introduction

A reputed Online Crowdfunding Platform and Website for fundraising of Social, Charity, Movies, Music, Personal and Creative causes. Visit us online!

The Challenge

  • The client has a keen focus on operational efficiency and wanted to be able to project KPIs for upcoming months

  • The client also wanted to derive a mechanism to compare KPIs against a target, so as to classify them as “Not Met”, “Met” or “Exceed”

1Score Approach

This was a classic use case for our OneScore KPI Forecasting
 

  • We started by doing data discovery sessions with client, which gave us a good understanding of their business and KPIs important to them

  • We went ahead with selecting KPIs based on the discovery sessions

  • Data aggregation was done and we prepared the data for implementation

  • We were able to setup benchmarking scores by deriving upper and lower limits, this helped in classifying the KPI’s as “Not Met”, “Met” or “Exceed”

  • We drew mock-ups for the dashboards the client wanted to see and finally presented the data in with visuals that were clean and easy to read

Benefits

  • Optimizing the operations based on projection

  • Better context for benchmarking KPIs

Case 4
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Case 4: Improving User Engagement

1Score Attribution Modelling Solution

Highly customizable, multiple algorithms that find the optimal model for conversion allocation

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Background

  • A reputed educational university was seeking to improve user engagement for their

  • marketing website, leading to conversions.

  • They were keen to understand the importance and impact of each page in the conversion cycle in order to improve content and maximize conversions thus increasing ROI.

Approach

  • Data Prep & Manipulation
    Sessionised Clickstream data containing pages visited and conversion status was transformed into a frequency based page path conversion dataset with combination of different sequences of pages visited.
     

  • Attribution Modelling:
    Different algorithms: ranging from Heuristics to Markov order methods were tested to arrive at the most optimal model for assigning credit to each page.

Results

  • Model Selection: Markov model was selected for giving the optimal attributional credit to each page using the channel attribution package in R
     

  • Transitional probability: The model yielded probabilities of moving from one state to another in the page path sequences with order 2
     

  • Model Comparison: Conversions and Monetary Value assigned to each page by multiple models
     
  • Removal Effect: Importance of each page is explained by the removal effect : the decrease in conversions once that page is removed from the journey
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