The digital path to purchase has had a significant impact on retailers. A record number of brick and mortar stores have closed in the past few years. To compete in the digital marketplace, retailers must have an effective omnichannel strategy. Enterra can help. Our Digital Path to Purchase solution enables retailers to understand customers and the products they desire. We combine advanced Big Data Analytics with insights-driven recommendation engine to identify consumer preferences in targeted locations.
Although retailers know they must master omnichannel operations, company COOs struggle to get omnichannel marketing and operations “right”. This is because there are different ways to handle omnichannel distribution (e.g., online sales using distribution centers and on-line pick-up in store), and keeping on top of things can quickly become complex. Cognitive computing can help deal with this complexity and turn challenges into opportunities. Operational systems need to be integrated, with 360° visibility of customer transactions, in order to ensure the best possible customer experience. Customers today are truly kings. They have the ultimate decision when it comes to retail format and engagement model. The Enterra System of Insight and Actions can:
Provide Omnichannel Commerce Orchestration for all customer transactions balancing retail desire with retail margin objectives
Help executives make decisions on a much broader set of data, from up and down the supply chain
Conduct complex market basket analysis with digital behavior to perform sophisticated digital path to purchase (e.g., Next Best Offer, “Inferred” Recommendation, Optimized Promotions, etc.)
Employ subtle human decision-making to adjust exceptions as well as your best experts
Retailers can use the Enterra System of Insight and Actions to improve profitability, as a result of a superior balance of tailored assortment, price and features. Personalization can enhance the customer experience and loyalty programs can become more effective. Most importantly, however, improved fulfilment optimization using automated adjudication of exceptions against a balanced set of objectives will ensure customers get what they want when they want it. Retailers will know they’re doing a good job with improved, detailed tracking of actuals versus plan for continuing a course of action.
Retail Shrinkage is a serious retail challenge, especially when its causes can’t be accurately determined. An estimated 2.5% of revenue can be lost depending on the channel. Out-of-stock situations are another inventory challenge facing retailers, with estimates ranging between 6% and 8% of items in total store inventory being out of stock at any one time. Sometimes the problem is as simple as not knowing where the product is located (e.g., is it in-store but off-shelf?). For a retailer to have an automated replenishment process, having an accurate inventory is critical. All these factors lead to decreased sales and higher inventory costs. Our intelligent inventory management system:
Detects and predicts the many different risk-signals and patterns of shrink by item
Attributes the causes and determines the environmental conditions of shrink
Can estimate the likelihood of an item being in-store but off-shelf
Alerts store management to physically verify and correct
When inventory accuracy improves so does on-shelf availability, while reducing out-of-stocks. Additionally, by identifying the patterns and causes of shrinkage, they can be addressed. Better inventory accuracy helps retailers lower the markdown budgets, rapidly identify and resolve in-store issues and improve product inventory.
Supply chain professionals are struggling with the synchronization of supply and demand. This should come as no surprise. Siloed local optimization and decision-making leads to misaligning of overall enterprise goals and, often, to misunderstandings between divisions. This can result in a huge amount of human processing of exceptions, resulting from the lack of agility in systems of record.
Although the data probably exists that could make optimization a reality, it is often not harnessed to enhance supply chain decision making and execution. With the Enterra System of Insight and Actions, retailers can:
Define one set of enterprise goals to keep optimization and decision-making across planning functions aligned
Encode the decision logic of the best human decision makers as well as rules from the system. This mitigates the risk of losing key personnel (i.e. loss of tribal knowledge) and enhances automated processes
Employ subtle human decision-making strategies to automatically adjudicate exceptions as well as your best experts
Make decisions on a much broader set of data from up and down the supply chain
By integrating data and making it available to everybody who needs it, the Enterra System of Insight and Actions can help create alignment across silos. This will result in more “perfect orders” and fewer out-of-stock situations. Other benefits include reduced transportation costs, reduced inventory costs and improved labor scheduling. Because it leverages machine learning, the System of Insight continually learns and adapts.
Companies often struggle to offer their customers the optimum product mix, at the right price, with the right features, to maximize category growth and profitability. The sheer scale of product/package combinations can overwhelm category management teams. Today, developing the right planogram is an expensive process and requires a high degree of manual effort. Truth be told, no amount of manual effort can keep up with the complexities of today’s category management system.
Add to that the complex nature of dynamic consumer decisions and the analytics required confound the abilities of traditional mathematics to isolate the effects of buying. At the same time, rising retail pressure continues to exert a downward pressure on profit margins. Now, with the Enterra System of Insight and Actions, retailers can:
Leverage unique and proprietary capabilities to model and disentangle complex interdependencies, as well as drive product margins including mix, price and features
Consider much broader data sets including consumer attitudes and environmental context (e.g. , demographic, weather, climate, seasonality, etc.) in which decisions are made to improve insight accuracy
Solve for unique category solutions including multiple vendor products and funding
The Enterra Category Management Intelligence SystemTM results in improved profitability due to a superior balance between product mix, price and features. Retailers are happy because they enjoy improved GMROI. The customers are happy because they can find the products they want at prices they can afford. The Category Management Intelligence System reduces the cost to create category management plans and provides detailed tracking of actuals versus plan for continued course correction. Just as importantly, the System results in improved insight as to “why” the plan was different than the actual performance.