Why Customer Analytics Is Now More Essential For The Consumer Durables Industry :


    Originally Posted: Talkcmo

    The Covid-19 pandemic is testing the consumer durables industry in ways few have seen before, with businesses struggling to capitalize in an altered buying environment, predicting demand, and coming up with better ways to manage the supply chain. Other challenges exposed by the crisis are labor shortages, import/ export restrictions, inventory management, route optimization, last-mile delivery, etc.

    The need of the hour is – to digitize fast and make use of a data-driven analytics framework and connected planning approach to navigate successfully, adapt, and stand out in a competitive market with new players entering new segments every day. Many companies now view customer analytics as their biggest competitor weapon in a Covid-19 world.

    Why customer analytics matters

    Customer analytics helps identify opportunities along the entire customer journey to guide and influence purchase decisions. With customer analytics, it is possible to get insights into consumers’ decision journey and their motivations, as they move from brand awareness to loyalty and purchase.

    Additionally, it can also help with curbing customer churn, increasing sales, and reducing campaign costs, thereby increasing the return on investments. Right from pricing strategy to competition analysis, customer analytics can serve essential use cases that can inform strategic decision-making.

    For example, customer analytics can enhance sales and marketing decisions by answering crucial questions such as;

    1. whether consumers are prioritizing certain goods versus others

    2. combining sales data with online reviews and feedback

    3. what proportion of purchases are done on impulse?

    Customer analytics also enables brands to see whether customers are purchasing in-store or are back to buying online in a Covid-19 environment and how this plays out across geographies. For instance, a consumer in Mumbai might be wary about going into a store – especially in a hyper-market climate with centralized air conditioning – but goes anyway because the need to buy a refrigerator in-store is high as she/he might have put their decision on hold for over six months.

    In unique scenarios, such as these, the positioning of a brand needs to change based on customers’ altered buying preferences, and customer analytics can help determine all of this.

    With customer analytics, companies can now leverage where their customers will purchase (channels), what they will buy (product mix), and when they will buy (predictive analytics).

    Additionally, companies can leverage this information to model (predict) the consumer affinity for any particular segment of their offerings.

    In many instances, companies suspended new orders because they couldn’t keep up with the rising demand. A sound data-backed strategy can help maximize capacity and build greater trust with consumers with the right communication via the most appropriate channels.

    A journey into the mind of the digital-age consumer

    A point to consider is that retail touchpoints have been affected considerably due to Covid-19, restricting consumers from physically experiencing products before purchase. Companies can now focus on enhancing digital experiences on their online channels to gain traction and use emerging technologies to guide consumers towards making a purchase.

    For example, virtual assistants can also be used on the shop floor to assist shoppers and give them a 3D view of a product while maintaining physical distancing. This helps merge the shopping and product experience seamlessly. Consumers are also finding themselves using more user/ influencer reviews before making a purchase.

    Furthermore, given netizens’ propensity to update social statuses on what they are looking for, what they liked/didn’t like, etc., it presents a treasure trove of information for brands to identify trends. However, new data sources such as social media and influencer marketing, give its own set of challenges, such as analyzing free-form text, videos, voice chats, etc. It is this very unstructured data that can be interpreted as significant sources of information to gain a competitive advantage.

    Designing smart customer analytics decision systems

    Some other use cases track out-of-stock situations, analyzing category performance by viewing pricing and segmentation, and maintaining transparency across the entire supply chain. Here are some key trends in customer analytics and connected planning shaping the future of the consumer durables industry;

    Change in buying behavior: Today, hygiene has become more important than pricing. And now that we find ourselves on this road, how is the entire hygiene experience going to pan out? Secondly, what happens when a user wants to return a product, especially perishables? A lot of trust and transparency have come into the entire buying/ selling cycle – consumers will have to go with the basis that the perishable product was handled with safety precautions.

    Change in spending capacity and power: The shopping landscape has changed dramatically;

    1. this pandemic has put a pause on consumers’ urge to spend impulsively

    2. it has resulted in a drop-in sale of products such as designer lights/ fans because renovations are on hold and people are instead saving their capital

    3. while a couple of months ago, shopping was on a massive decline, we are now seeing people going back to spending. However, this might not be the scenario two months down the line

    Hence, companies need an agile planning platform to plan frequently and anticipate changes. Predictive analytics creates an agile planning framework and future-proof decisions to mitigate the impact of supply-side constraints or demand shocks.

    Smart innovations: In-store analytics can help create personalized offers and optimized inventory levels. RFID tagging enhances customized shopping for customers, and AI-powered intelligent systems can transform POS-based systems. End-to-end value chain automation and managing inventory through automated demand fulfillment can also be achieved for a lean operating model.

    Now is the time for the consumer durables industry to review their operating models and use technologies to withstand any future disruptions. Consumer durables companies need to realize the value of effectively analyzing the volume of new and existing data to understand their customers better.

    Customer analytics is no longer a nice-to-have capability but rather a must-have if brands want to impact growth, especially in a post-COVID-19 world positively.

    Customer analytics is no longer a nice-to-have capability but rather a must-have if brands want to impact growth, especially in a post-COVID-19 world positively.