Aligning Data Science Initiatives with Business Goals

Data science provides a foundation to optimize marketing spend and increase revenue for retail brands. We are starting to see over the past 5 years, more and more companies utilise data to answer most business questions. Yet most companies use basic data tools. During

the pandemic, McKinsey estimates, the 25 top-performing retailers — most of whom are digital leaders — were 83% more profitable than laggards and took home more than 90% of the sector’s gains in market capitalization. One of the reasons organisations, find it cumbersome to create a data science team, is the lack of right talent and tools. They fail to find employees who can bridge functional gaps between analytics and business.

To ensure that organisations can focus on their core business, we at Quest Digital have developed propriety AI software which can sync with most databases and provide real time insights. Our team is experience in working with a number of analytics tools and use-cases.

This blog provides a glimpse as to how we utilise data science tools at Quest Digital to connect data to revenue.

1. Data Requirements & Collection

2. Creating a data backed digital marketing strategy

3. Real Time Insights

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Data Requirements & Collection

The first step is to have clean data about campaigns, websites, consumer behaviours, etc. Data scientists utilise this data to find patterns and trends using machine learning algorithms and predictive analytics. Several use cases are drawn at this stage to understand what sort of data is needed and in what form. Data format, sources, content are clarified at this stage.

If certain data is not available or accessible, certain investments need to be made to obtain it from third-party vendors. If at later stages, there is hindrances in data gathering, then this stage needs to be revised again.

Creating a Data Backed Strategy

At this stage, we hold a discovery workshop with the clients to understand what problem they are trying to answer with data. How can it be presented so as to enable action from management. Various analysis such as sentiment analysis, customer lifetime value,

brand lift studies, search lift studies etc. In one of the use cases we utilised data to decide what creatives to be used across different countries.

  Real Time Insights

This is the most important part, wherein businesses can be provided with real time insights that can be used to optimize marketing efforts and create new cross sell opportunities.

By implementing data collection stack, building a data-driven marketing strategy, performing optimisations and providing actionable insights, marketers can significantly aid their clients to improve the effectiveness of their marketing efforts to align with business goal.  See what’s possible for your company today by reaching out to Quest Digital and getting a conversation started around data science, creatives, & analysis.