Having the right data intelligence at every stage of a retail product’s life creates a pervasive and positive impact for manufacturers, distributors, retailers, and customers. However, historic ways of managing data fail to provide the agility, scalability, and flexibility that all these organizations require.
According to Gartner, more responsive, scalable artificial intelligence (AI) must have the learning algorithms to pivot quickly and shorten the time-to-value. AI technology must be able to work with smaller, more specific data sets and adaptive machine learning (ML) so that actionable data drives change from the production floor to long-term customer loyalty programs. Let’s take a step-by-step journey to see how this works in practice.
On the Floor!
Production Floor Optimization
According to Supply & Demand Chain Executive, manufacturers have moved to a dynamic approach to better understand their customers. By combining operational data with information on products and consumers, they strive to improve customer experience and boost profits. Data intelligence provides manufacturers with a means to better understand demand in order to drive development lifecycles and quality programs.
This potentially results in real-time production adjustments in order to capture more sales as well as experiencing fewer returns and complaints due to higher quality performance. This, then, pervasively impacts the cost of returns and restocking as well as call center loads.
In the Chain!
Supply Chain Visibility
Gartner reported that by 2023, half of all “global product-centric enterprises will have invested in real-time transportation visibility platforms.” This fact illustrates the importance of data intelligence throughout the supply chain
After manufacturing is complete and products leave the facility to be stored at a warehouse or moved to a distribution center, all parties typically have little visibility into the status and movement of the items. Data intelligence can be supplied through a wide range of vendors, but care must be taken to consider regional and modal coverage as well as integration and alignment with current carrier and transportation networks in order to optimize results.
Internal supply chain data intelligence, such as information contained within a retail chain’s own inventory system, can provide additional visibility into revenue or cost-saving opportunities. For example, if one location finds that a new product is failing to sell in a local market, yet a different store is sold out, that product can be moved quickly and directly from the first to the latter, saving transportation costs as well as maximizing the revenue from those.
In the Store!
In an increasingly “phygital” world, the demands on traditional brick and mortar stores to up the ante on customer intelligence are real. According to Forbes, the essence of the phrase “phygital” — the combination of physical and digital for enhanced experiences – requires the creation of an omnichannel, psychologically astute, multi-revenue customer journey.
Advanced analytical tools today are enabling offline retailers to deep dive and respond to varying market patterns by dynamically adjusting pricing, promotions, and assortments within the physical store. Although specific point solutions attempt to cater to this market’s need, the requirement for a unified solution that looks at customer-centric innovation holistically, both in the physical and digital realms, is more prescient than ever.
In the Mind!
It’s a well-known fact that customer acquisition is far more expensive than customer retention. An article in Forbes reported that it can cost five times more to attract a new customer than keep an existing one and that simply increasing retention rates by 5 percent can increase profitability by 25 percent up to 95 percent according to management consultant Bain & Company.
Data intelligence helps create customer stickiness, fueling a healthy addiction to a company’s brand. When retailers can accurately and frequently speak to that “audience of one” by offering products or services before customers even realize they need or want them, they create a reputation of truly “knowing” their customers.
AI and adaptive ML can effectively create a dossier of each customer over time, delivering personalized discounts, customized bundles of products, and an accurate reordering schedule. The pervasive impact is a loyal customer that continues purchasing from the same company consistently over years or even decades.