In this special guest feature, Greg Ng, VP of Digital Engagement at PointSource explains how AI is helping companies tailor the user experience to each customer’s specific wants and needs.
In this contributed article, Samuel Lim, CEO & Co-founder at Reebonz.com, discusses data’s role in opening up luxury to a broader market: aka The Chanel Effect.
I recently caught up with Paulo Sampaio, Data Scientist at EDITED, to talk about applying machine learning, neural networks, natural language processing, and big data analytics to the retail industry. Paulo and his team are applying neural networks, machine learning and other models to analyze over 520 million products in real-time across 42 countries to make gradual distinctions in clothing styles, sizes and categories.
It is becoming more and more apparent how data analysis is driving e-commerce revenues. And this growing importance has forced e-tailers and e-commerce firms to hire more data scientists in order to better understand how customer engagement impacts revenue and sales. This assessment comes from SOASTA, the leader in performance analytics, who reveals that data analytics is important in all aspects of the organization – from digital transformation to digital performance management.
SOASTA offers five ways data analytics will storm the stage in 2017.
In this contributed article, tech writer Rick Delgado, discusses how the retail world is jumping on the big data analytics bandwagon. Analytics are being used at every stage of the buying process — from predicting popular products to pricing and figuring out what to sell to customers next. Retailers aren’t holding back on what big data can do for them.
Whether Artificial Intelligence (AI) is something you’ve just come across or it’s something you’ve been monitoring for a while, there’s no denying that it’s starting to influence many industries. And one place that it’s really starting to change things is e-commerce. Look at some examples of how leading online stores have used AI to enrich the customer buying experience.
Set against a backdrop of declining profitability and significant changes in consumer lifestyles, retailers are under pressure to deliver the best freshness and optimal availability to their customers without the ability manage cost to serve. Typically, 40 percent of grocery revenue is driven by fresh, according to the latest McKinsey report: get this right and the rest will follow, including the customer and profits. Grocery has traditionally struggled to deliver the right customer experience in fresh without forsaking margin.
Amplitude Study Finds that “N Day” Retention Metric Underestimates the Percentage of Users who Return to Apps by a Factor of 3.5X
Amplitude released findings from a study of retention data collected from its popular analytics platform and found that the most commonly used retention metric, known as ‘N Day,’ underestimates the percentage of users who return to apps over time by a factor of 3.5x.
EDITED, the source of real-time data for brands and retailers, has launched the first software feature to help companies capitalize on the billion dollar activewear market.
Today SGI announced that enterprises can now leverage the Intel-based SGI UV 300H server in a multi-node cluster (scale out) to run SAP Business Warehouse (SAP BW) on SAP HANA or new SAP BW/4HANA. Unique to SGI, the cluster nodes can later be reconfigured as single-node systems with 1 to 32TB of shared memory (scale up) to run SAP S/4HANA and other real-time applications. “For large enterprises that plan to migrate to SAP S/4HANA but wish to begin their journey to SAP HANA with SAP BW, our new SGI cluster offering is unquestionably the optimal solution,” said Jorge Titinger, president and CEO, SGI. “The scalability of the SGI UV 300H architecture coupled with our expertise in mission-critical environments provides an ideal path to real-time business with SAP HANA.”