Consumer industry trends and data analytics

Date: January 2022
Author: Boonsom Jarusiritarangkul, Malee Ekviriyakit

Before the COVID-19 outbreak, the consumer product sector was tapping into the big data and data analytics realm while it now is evident that with the fundamental changes in consumer behaviours brought about by the pandemic, the adoption rate of advanced analytics has been accelerated. The exchange and sharing of data have never been more prolific and integral in every day’s life from delivery services to ecommerce. Interestingly, up to 80% of the vast pool of customer data collected by consumer centric businesses and the internal data within the corporate value chain are yet to be explored. Data analytics, especially in the consumer product industry with its massive brand and product options, has nowadays become pivotal for companies to maintain or gain a competitive position within the industry from operational and business standpoints. 

Changed business operation and consumer behaviours 

Immediate responses and solution provisions to tackle the pandemic have trained people to be used to real-time data and cloud servicing.  

  1. AI tools for marketing and customer experience 
    Artificial intelligence and data are now used to provide a timely offer to customers along with enhanced post-purchase customer experience. Based on data of customer demography and preferences, predictive AI can make personalized product or service suggestions in time or even before the need. AI can also inform customer service agents instantly AI when customers might encounter problems. Deloitte’s survey among 11,500 global consumers, reenforced the idea as it is found that timely offers and knowledgeable customer services are key benefits from AI.

  2. Digital and remote service
    Brands now engage consumers through a more hybrid approach that incorporates both traditional and digital channels. Remote digital services such as telemedicine benefit from the social distancing mandate while consumers, especially younger generations, would like to maintain the services post COVID-19. 

  3. Data analytics and improved internal work process
    Predictive models for inventory as well as budgeting can streamline the value chain, improve the work efficiency without human errors and ultimately reduce time and cost consumption.

Big data and future direction in the consumer industry 

Consumers are more open to share personal data and innovation which is beneficial to business to identify trends. There are several evidences of company using big data to identify trends, the following are the examples from consumer industry;

  1. The ever-growing expansion of choices and selling-channels
    The plethora of choices are evident with grocery stores stocking more than five times the products as they did in 1990s while consumers at present have gained familiarity with mixed-channel shopping through physical stores, e-commerce, digital apps, social commerce, and marketplace platforms. The exposure to the multitude of options has led to a decrease in brand loyalty and market share fragmentation along with decisions by company to premiumise their products for higher profitability.
  2. Digital advertising incessantly becoming more expensive
    The higher digital traffic competition coupled with the increasing delivery and labour costs have led to the increasing digital advertising costs. This will also put more pressure to the online direction with companies sustaining lower and lower margins. 
  3. There are places for physical stores
    Successful retail stores post COVID-19 outbreak are stores that have become smaller, been located closer to consumers and offered online shopping or delivery options for increased convenience to access. Those failing to offer a more convenient product access are at risk of being left behind in this era where things can be done through swipes of a mobile phone.
  4. New business models
    Similar to the increasing number of choices for consumers, there are increasing number of new business models such as direct-to-consumer, food service alternatives, subscription services rentals, marketplaces and resale being adopted by companies with businesses striving for market shares. With the unprecedented factors and challenges at present, companies are more open to take risks in trying and adopting new models. For example, in the US, the combined alternative business models in apparel (such as rental, resale, subscription, and flash sales) gained 1.4% of incremental market share between 2016 and 2018 and are projected to continue to amass an additional 1% of apparel market share annually each year through 2023.
  5. Convenience is key
    In order to succeed in this fast-paced era, companies that win in convenience have the edge over the peers. Understanding target customers and the types of convenience that suit their preferences from data can lead to a tangible and actionable strategy.  Store footfall by square footage at US retail stores has dropped by 4.4% in 2018 while he growth of small-format stores such as convenience stores has been a driving force in the long-term decline in store sizes.
  6. Healthy and sustainable consumption might not be for everyone
    The trend of healthy and sustainable products might be deceiving as products marketed as healthy and sustainable tend to be more expensive and can be accessed by consumer with higher income. The majority of the market remains dominated by consumers with financial constraints.

The competition in the retail and consumer landscape has never been more intense with COVID-19 bringing about challenges in every business operational aspect and consumer behaviours that have forever been changed. The data-centric analysis of the industry has led to the identifications of a number of emerging trends within the industry. With lower brand loyalty and focus on convenience, companies that trail behind the rest of the pack in embracing data or adapting to the subsequent insights might eventually find themselves too far behind to catch up in this age of information technology and agile businesses. 

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