Share

Data oriented teams analyze the statistics of the business and provide an understanding or interpretation of what their current status is and how that data can be used to achieve their business objectives. With the correct skills and values, a data-driven team can (1) guide a business through business cycles/economic conditions and (2) improve other business aspects like production, supply chain management and marketing.

Being data-driven has become as important as being “innovative”, “diverse”, and “socially responsible.” It has undoubtedly become one of the most admirable features of organizational culture, and an imperative feature of e-commerce brands. Major decisions, particularly those related to marketing and growth, can no longer be based on intuition. Evidence-based decision making is key, and for e-commerce and marketing teams, that means effectively understanding and analyzing vast amounts of data captured and stored in marketing and sales channels and other technologies. E-commerce and marketing leaders are now tasked with building teams that are data-driven and comfortable with utilizing data effectively to grow and scale online. 

Nonetheless for many companies, a strong, data-driven culture remains elusive, because many find it hard to build data-driven teams and at times, teams also feel under-equipped to use data for decision-making.

One company that strongly believes in being data-driven is IGP in India – formerly known as Indian Gift Portal. This popular gifting company has maintained a stable presence even during these unpredictable times because of its investments in building data-driven teams - particularly data-driven marketing teams.  

When speaking to Vrinda Aggarwal, Associate Vice President of Marketing at IGP, she highlighted the following factors act as imperative to building data-oriented teams in e-commerce companies:

  • Establish a set of values that team leaders and team members can use to gain a clear understanding of how to set goals and practices that ensures they are using data in the best possible way.
  • In every business function and process, set up a way to capture data and use data from the past to inform decisions that affect the company’s future.
  • Invest in the right tools that allow teams to structure data in ways they see fit so they can explore various ways of using data to make better informed decisions.

For example, IGP has made their marketing team more data-oriented by:

  • Standardizing KPIs
    • By standardizing KPIs across the marketing team, both leaders and team members alike are clear on the common goals they are working towards achieving and they have a good understanding of the underlying assumptions, definitions and other reasoning behind those KPIs and goals.
  • ‍Making data more accessible
    • To promote a culture of being data oriented, IGP ensures that any data collected is easily accessible to the teams for interpretation. Team members are given the freedom to use the data as they fit to analyze and develop solutions and insights that would be useful to achieving business targets and goals.
  • ‍Breaking down marketing activities, funnel stages, processes, and workflows:
    • By breaking down the various aspects of marketing, team members find it easier to associate data with each activity, stage, process, or workflow, and this encourages them to collect and use data to improve their efforts and problem solve to avoid losses.
  • ‍Using the right technology
    • Marketing related technology, including analytics, is rapidly advancing to help teams become more data oriented. Indeed, many marketing teams are not fully utilizing all the data captured and stored in marketing related technology like Google Analytics to find high intent audiences to target on ad platforms like Facebook.
    • Additionally, given that companies like Apple and Google are implementing significant changes aimed at eliminating the use of third-party cookies, it is important for marketing teams to find technology that enables them to use “customer first data” and reduces the need for data collected by third party cookies (see below for explanations of third-party data and customer first data).
    • Using technology like Alavi.ai that only needs customer first data, can help marketing teams become more data-oriented and implement marketing strategies that helps them achieve higher returns and win the right customers.

The COVID-19 pandemic unleashed an unprecedented level of uncertainty on businesses all over the world. And what became quite clear is that businesses that had invested time and effort into building data-oriented teams were better at managing the positive and/or negative impacts of the pandemic than others.  
Vrinda mentioned that IGP’s marketing team, for example, was already using historic data to develop marketing strategies and action plans. Therefore, with data gathered from the previous years, IGP was able to plan a 12-month business strategy, despite the many uncertainties. Failing to encourage data-oriented teams can cause businesses to cripple when things shift into unfamiliar territory.

Advice to Small and Medium-sized E-commerce Businesses

When it comes to building data-oriented teams, small and medium sized businesses have different experiences. Here are a few examples:

  • Some companies invest in technology without tracking any data, and as a result they are unable to benefit from the technology they invested in.  
  • Some companies track data, but they do not know how to use it because they have not considered using technology can help them use their data.  
  • Some companies invest in the most advanced technology available, but their teams are underequipped to use that technology, and as a result they do not get the returns they expected.  

When it comes to building data-oriented teams in small to medium businesses, Vrinda advises that these companies start by first setting up their tracking. Small to medium businesses should track everything and doing that will ensure that all their data is being collected and stored. Once data is collected and storied it can always be used in the future to understand key trends and identify challenges and opportunities. Additionally, if a company’s tracking is set up properly, its teams can even conduct some simple analyses to understand trends and develop data-driven strategies.

Once tracking has been properly set up, companies can consider including technology to make sense of all their tracked data. And prior to investing in any technology, companies and/or teams should have a clear idea of what they want to gain by using technology. For example, in the context of marketing teams, by using technology to analyze their data, do they want to find out new audiences they should target in the next 7 days to fill their top funnel, or do they want to find their most profitable remarketing audiences, or do they want to know which of their existing customers are most likely to spend big in the next 30 days? Having a clear idea of what the technology is supposed to find using the tracked data will give the team a better chance of successfully using the technology to build data-oriented teams that can deliver impressive results.

NOTES:

Third party data
Third-party data is tracked by third-party cookies. Third-party data allows a company to learn about a web visitor's overall online behavior, such as websites they frequently visit, purchases, and things they have been interested in on other websites.  

Customer first data
Customer-first data is data that is sourced directly from a prospect or customer. This data is both zero-party data (information that someone proactively gives to you, like their email address, phone number or birthday) and first-party data (information captured by a company about someone’s behavior when visited that company’s owned properties/assets, like pages on their website). All customer-first data can be used by marketing teams for personalization and targeting on ad platforms.

‍

Use Alavi and Scale Without Fear

Developed for small and medium businesses, Alavi is a martech application that performs predicative analytics on your customers’ behavioural data. By combining AI, machine learning and automation, it helps digital marketers better understand their audiences, improve their targeting, and scale confidently profitably.

Alavi has a proven record of helping brands in a variety industries grow their revenue online. It has a very short time-to-value and is easy to setup and use.

Get a Demo Now

To contact us,
Please email
thamaliw@alavi.ai