- “Yet with SAP’s 2018 Digital Transformation Executive Study finding just 3 per cent of retailers have completed digital transformation projects, most of which focused on efficiency and cost cutting, there’s clearly still a long way to go before brands successfully harness digital for more disruptive innovation in the retail experience.
- Again, however, only a small percentage of data is being used by retailers in decision making. While these organisations tend to collect as much data as they can, squirrelling away for future use, they’re still not able to ascertain its significance, Schneider agreed.
- An example is Adidas in Russia, which used existing cameras plus RFID readers and RFID tags on garments and products to improve real-time inventory accuracy in its physical store from 60 per cent to 99 per cent. Adidas is now looking to rollout the approach globally.”
- “Despite their heroic work to date, financial services firms will face the same competitive and regulatory challenges in 2019 as in the past years.
- Navigating around the three-headed beast—competitive disruption from other established firms, fintechs and new digital-only banks—represents another big issue.
- Thus the overarching mission for at least the next year involves digital transformation. Enter artificial intelligence (AI), which promises to forever transform banking and propel the industry deeper into the digital age.
- Less analytically mature organizations are just catching up to traditional “big data” challenges
- At the same time, consumers are becoming more savvy and cautious regarding the use of their data.
- Banks will continue to adopt AI and machine learning technologies in 2019. Why? Perhaps the most urgent reason centers on “in-the-moment speed.” Despite having plenty of customer data, banks by and large lack the capacity for instant analysis and interpretation.
- Inexpensive technology to process billions of transactions is commonplace—but extracting value and insights from that data remains difficult.”
One common data management theme has emerged in 2019: that data equals the new energy source that runs modern businesses
- “In the US, for example, ecommerce currently accounts for approximately 10% of all retail sales, a number that’s projected to swell to nearly 18% by 2021.
- Financial analysts predict the retail giant (Amazon) will control 50% of the US’ online retail sales by as early as 2021,
- In order to shift ecommerce from a product-centric to a customer-centric model, ecommerce companies need to invest in unifying customer data to inform internal processes, and provide faster, smarter services.
- Data becomes valuable as it provides insights that allow companies to make smarter decisions based on each consumer
- Data holds the key to this revolution. Instead of trying to force their agenda upon customers or engage in wild speculations about customer desires, ecommerce stores can use data to craft narratives that engage customers, create a loyal brand following, and drive increasing profits.
- With only about 2.5% of ecommerce web visits converting to sales on average, ecommerce companies that want to stay competitive must open themselves up to big data and the growth opportunities it offers.”
- “over $1 trillion of today’s financial services cost structure is exposed to replacement by machine learning and artificial intelligence (AI).” Meaning that in the near future, AI will have a huge impact on how financial services enterprises run and do business.
- Today, the main use case for AI in financial services is in the contact center – shifting calls to self-service or a chatbot to lower costs.
However, there is a lot of potential to use AI for higher-value conversations. This is especially true when combining AI with another hot technology – video.
In fact, the latest edition of our annual video banking report highlights that 82% of financial institutions plan to offer video banking services.
- Chatbot-to-human escalation
- Real-time sentiment analysis
- Simultaneous interpreting
- “Technology now accounts for a whopping 29 percent of the total marketing expense budget, making martech the single largest area of investment when it comes to marketing resources and programs
- Investments in AR and VR, a small segment of AI, are expected to grow from $11.4 billion in 2017 to $215 billion in 2021, according to IDC.
- Meanwhile, 56 percent of senior AI professionals peg a lack of qualified workers as the single greatest barrier to AI implementation (Ernst & Young).
- The volume of data created worldwide is growing at a staggering 40 percent per year, feeding a near-unimaginable level of intelligence into organizations attempting to make sense of and activate it.
- It’s the next step in automation that gets exciting, and that is the combination of automation and AI. Intelligent automation takes the efficiency and productivity of automation and layers on data analysis, decision-making and even prioritizing next steps.
- Marketing and customer analytics have been named by 40 percent of CMOs as the top capabilities needed to support the delivery of their marketing strategies over the next 18 months.
- At least 99 percent of big data is not even analyzed, according to the IDC.
- Today, deep learning allows us to take massive and sometimes unstructured datasets and reap actionable, relevant insights.
- What’s more, predictive analytics activates those insights by facilitating real-time optimization, ongoing measurement, and further optimization.”
- “Gartner correctly predicted that by 2017, the CMO would spend more than the CIO on IT.
- However, the cost of acquiring a new customer is five times greater than that of retaining an existing one, and the probability of selling to an existing customer is 60 percent, while the probability of selling to a new prospect is 5 percent.
- As AI continues to revolutionize the digital landscape, marketers will increasingly depend on this technology to maximize consumer reach and sales
- AI within marketing technology means more effective customer segmentation, advanced and updated customer analytics and efficient marketing strategies. This will create a domino effect where businesses will want to compete in order to capture consumer demand, leading to the further rise of AI in marketing.
- Traditional marketing is shifting toward reliance on data analytics, virtual platforms and machine learning through 2019.”
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“Reportedly, the move will help Flipkart to deliver real-time pricing and product analytics to its seller partners. According to an ET report, industry insiders have hinted that Flipkart bought the retail intelligence startup for around $30-40 million.
Upstream Commerce offers a suite of products related to predictive price optimization, pricing intelligence, lifecycle intelligence among others. In December 2016, Israeli startup which registered a 385 percent growth rate over the last three years, was also named Deloitte Technology Fast 500 EMEA list, a ranking of the 500 fastest-growing technology, media, telecommunications, life sciences and energy tech companies in Europe, the Middle East and Africa. The startup was backed by YL Ventures.”