How D-to-C and E-Commerce Brands Can Leverage Augmented Analytics to Streamline Operations
E-commerce sales have accelerated dramatically throughout the pandemic. Gartner found that nearly half of consumers increased their online shopping last year. More transactions mean more generated data; data that e-commerce providers can use to improve customer engagement and overall business performance.
With augmented analytics, e-commerce players can accelerate the process of turning data into actionable insights by automatically sourcing data for analysis and surfacing important findings, instead of having data experts manually sift through the data. Decision makers at e-commerce companies can then go beyond just monitoring key metrics via dashboards with the ability to ask questions in a search interface using natural language. This helps them obtain the “why” behind the “what” with simple questions like, “Why are denim sales down in Atlanta?”
Here are four ways augmented analytics can help e-commerce retailers optimize their data as efficiently as possible:
Analyze Shipping Delay Root Causes
Shipping delays are frustrating to customers and vendors alike. Root cause analysis is difficult; as we’ve seen, supply chains are complex, interdependent systems, and manually tracking millions of packages is near impossible.
Augmented analytics can perform key driver analysis to identify real-time root causes of delays by ZIP codes, shipping lanes and other key data points. This allows brands to discover which factors cause the most difficulty and proactively remedy the issues to reduce future delays — improving customer experiences at scale.
Enhance Operational Performance Via NPS Insights
Net Promoter Score (NPS) is a critical data point brands use to understand customer satisfaction and enhance brand affinity. Typically, data analysts need to manually collate, analyze and run regressions of NPS scores alongside customer service issues and demographics to find patterns that can improve the shopping experience.
Augmented analytics simplifies this analysis by automating the discovery of the most relevant findings across survey results, customer attributes and transactional data in order to pinpoint operational improvements across the entire fulfillment process. One leading retail firm used automated insights to discover a positive correlation between high NPS scores and selection of more expensive shipping options by customers. This type of insight can inform potential offerings. For example, consumers who opt for next-day delivery have more positive experiences and are more likely to promote that brand as a result.
Create More Effective Consumer Promotions and Incentives
Brands are always looking for ways to enhance customer loyalty. The key is not only to provide good experiences to boost affinity, but also create reasons to return. By leveraging augmented analytics, brands can offer effective promotions and incentives to particular consumers based on historical purchasing activity.
Over time, e-commerce platforms can create corrective feedback loops between promotions and customer spend outcomes to continuously improve the model. By tracking how often returning customers take advantage of a promotion, brands can determine which campaigns are performing well.
Improve Inventory Management
Merging logistics data with inventory management systems and valuable third-party data (e.g., weather and consumer patterns) is time consuming. Analyzing key drivers is often limited to pivot tables, and multivariate analysis is out of reach. Augmented analytics can easily automate data pipelines from internal and external sources, as well as look across all variables (not just subsets) for patterns to determine inventory needs.
For example, with augmented analytics, a food delivery company can determine how much of a product it will need (without overordering) and why demand for certain foods increases one month compared to others. These capabilities are especially important for brands that sell perishable items and need to ensure products are fresh.
Gain Data-Driven Insights With Augmented Analytics
Rather than spending inordinate amounts of time building backwards-looking dashboards to monitor metrics, e-commerce providers are leveraging augmented analytics to gain real-time insights more efficiently into shipping patterns, consumer behavior, promotions, inventory and more. With this information, they can identify the specific, granular ways to streamline operations and improve customer experiences, resulting in increased loyalty and a better bottom line.
Ajay Khanna is the CEO and founder of Tellius, the first decision intelligence platform to handle ad hoc query and compute-intensive ML/AI workloads.
Ajay Khanna, CEO and founder of Tellius, a company disrupting business analytics with Search and AI, is a tech entrepreneur who has a passion for building disruptive enterprise products with an awesome user experience.
Prior to starting Tellius, Ajay was CTO & Founding member of Celcite, a fast growing telecom analytics and solutions company, that was acquired by Amdocs.
Ajay has over 25 years of extensive experience working in various technical, business. and consulting roles. He holds degree in Electronics and Communications Engineering.