Gib Bassett, Solutions Marketing Director, Alteryx

Gib Bassett joined Alteryx to lead marketing for supply chain, retail, CPG, and manufacturing industry solutions. He is passionate about helping business and technology leaders and their teams overcome challenges to achieving best-in-class outcomes with analytics. Prior to Alteryx, Gib worked in customer success at Salesforce, where he supported several top retailers throughout their cross-cloud digital transformation journeys. In prior roles he led go to market for retail and consumer goods big data analytics at Oracle, and global CPG retail and manufacturing industry marketing at Teradata. 


The COVID pandemic continues to pose significant challenges for supply chains globally. The Food Supply Chains and COVID-19: Impacts and Policy Lessons highlighted that consumers were left with empty shelves and prices were rising for retailers because of shipping disruptions, thereby raising freight costs due to expediting, and resulting in shortages of essentials. It was an inability to pre-emptively sense demand shifts while ensuring open supply lines that  led to many retailers suffering financially. However, there is a class of analytics solutions tailor made for the types of supply chain decisions dependent on moving quickly and confidently even in disruptive conditions.  

Drastic Digitization of Retail Businesses 

According to the 2020 McKinsey report on Perspectives on Retail and Consumer Goods, 96% of consumers have upgraded their buying habits, and 60% are predicted to switch to online shopping in the run-up to the holiday season and do so indefinitely after the pandemic. The pandemic, which caused an increase in e-commerce and expedited digital transformation, resulted in a paradigm shift in consumer behaviour toward online shopping for both essential and non-essential categories. Due to the changing business environment, retailers in all sectors and of all sizes are forced to rethink, adapt, and provide a cohesive consumer experience both physically and digitally.  

Many retailers have invested in alternative digital solutions to quickly respond to shifting market conditions in an effort to innovate and provide customers with the finest service. India Brand Equity Foundation’s study- Indian Retail Industry Analysis states that the online penetration of retail is expected to reach 10.7% by 2024 versus 4.7% in 2019. This would eventually lead to more storing and processing data on products, services, and consumers. This equips retailers with the opportunity to make use of their customer data and refine it further to get the insights necessary to future-proof their plans and emerge stronger and more flexible.  

In order to take advantage of this data, smart retailers have adopted Analytics Automation solutions as a means to equip data workers embedded in supply chains with the ability to respond quickly to changing market conditions. In this way, supply chain processes as diverse as demand planning and procurement benefit from improved visibility, responsiveness, and repeatability. 

Data Analysis Extending Roots in Retail 

Retailers collect various kinds of data: customer, transactional, operational, and inventory and pricing information. The same merchants, however, frequently struggle to use this resource practically to guide decisions, support market adversity strategies, and uncover possibilities to fulfil customers’ ever-changing tastes. Data science is crucial in this situation because it can be used to translate unprocessed data from e-commerce baskets or point-of-sale data into consumer behaviour insights. All retailers can produce data-driven insights by applying data science and analytics to this information. Businesses can use these insights to better understand the performance of product lines, develop individualised promotions to increase sales, or even create a more engaging and rewarding customer experience throughout the entire buying journey. 

Moreover, the use of external data to augment and inform all manner of supply chain decisions is associated with top retail performers. Unless overcoming the fundamental use of internal data, it’s not possible to leverage external data signals to gain a finer understanding of customer needs and behaviours, to say nothing of supplier capacity. Analytics Automation solutions provide a means to this end. 

Boosting Business through Data Analysis  

Retailers can benefit from adopting Analytics Automation software  to optimize their inventory and evaluate the extent to which the supply chain supports a great customer experience. For example: 

A. Tracking Supply & Demand 

To boost efficiency throughout their supply chain, for instance, companies might use past projections to help train predictive models that can optimize inventories and reduce wait times. Taking this a step further and looking outside to external data sources can greatly enhance the quality of a supply chain decision. Building this supply chain visibility can assist merchants in making backup plans, such as locating other suppliers in the event that their primary source is compromised. The focus needs to be on developing techniques to promote resilience, to anticipate demand and enhance supply. 

Considering recent disruption, it is now more crucial than ever to guarantee that goods are delivered on time, every time. To achieve this goal, it is essential to integrate analytics into procedures and operations throughout the whole supply chain. This will help to ensure that goods move swiftly from the manufacturer to the logistics partner and then to the client. These analytics can provide recommendations and other options to enhance delivery performance on both a micro and macro level, as well as help predict whether a product will reach its destination on time.  

B. Customer Shopping Experience 

Data analytics and automation play an important role in every step of the customer journey. From understanding customers’ behaviours, it is possible to predict not just the shopping trends but also how they affect the current demand and supply of products and services. A customer’s searches, wish lists, and previous purchases all make up customer data. Additional information like geographical location and purchase frequencies helps build a customer profile. Analysing customer data can help personalise the customer experience and better recommend products and services that align with their interests. This approach to utilising customer data can maximise sales in the present and help build a loyal customer base in the long haul.  

The Road Ahead 

All merchants, in one way or another, have access to data that can be utilized to get insights that have a big impact on business choices. This data may come from point-of-sale data or may even be as simple as counting the number of customer inquiries that come in. A misconception is that one needs enormous amounts of data to draw good conclusions, while many projects use tiny datasets to produce enormous value – quality over quantity.  

Retailers must harness and use the power of data in their decision-making if they want to strengthen their business and to build that competitive edge in this digital era. Many companies are sitting on a goldmine of data, even though they may not be aware of it. The ability to access, analyse, and democratize this data will be crucial for maintaining the fundamental contract between buyer and seller. It is now, more than ever that retail needs to maximise the use of the digital boom to effectively grow their business and stay relevant.  

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