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Informatica launches Intelligent Data Management Cloud for Retail



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Informatica, an enterprise cloud data management provider, has unveiled the Intelligent Data Management Cloud (IDMC) for Retail with new cloud-first, cloud-native capabilities built to help the retail industry drive innovation and business value.

The retail industry has had to pivot to a digital-first strategy powered by the Cloud in matter of weeks in light of the global pandemic and this acceleration to the Cloud is predicted to continue post Covid. The retail industry will generate more data in the next three years than in the past thirty, driving them to invest in cloud-first solutions that can unify customer data across multiple sources to derive a single source of truth. IDMC for Retail is the first and only cloud-neutral Data Management Cloud for the retail industry enabling retail organisations to deliver digital-first experiences to their customers and driving omni-channel revenue growth.

The Hershey Company, a snacking powerhouse with over 90 brands and $8B in annual revenues, keeps its 128-year-old company thriving with its long-term view on growth and differentiated capabilities. The company recognised the importance of modernising the way trusted data is delivered to the business, seeking a solution that is easy to adopt and would deliver immediate value. “Informatica was able to demonstrate the power of the Intelligent Data Management Cloud platform, demonstrating out of the box connectivity while also having the ability to tailor UI’s to both technical and business users,” said Ryan Gelberd, Enterpirse Data and Technology, the Hershey Company. “The partnership will allow Hershey to deliver trusted, governed data to their users with the utmost confidence.”

“The Cloud has empowered us to engage with our customers in meaningful ways never before possible and capitalise on real-time moments to up-sell and cross-sell while maintaining high customer satisfaction scores,” said Gary Desai, CIO, Discount Tires. “Informatica’s Intelligent Data Management Cloud for Retail will be a game-changer for retail companies especially with its ability to efficiently manage the supply chain and inventory in the current climate.”

IDMC for Retail enables retail companies to deliver highly personalised, digital-first customer experiences across all channels, at-scale so retailers can respond to dynamic, real-time customer needs by unifying customer data across multiple domains, systems and multiple clouds in some instances.

IDMC for Retail helps:
• Improve customer profiles with clean, consistent and complete information
• Increase self-service with search and exploration of customer relationships through both network and hierarchy views
• Efficiently acquire, manage and publish relevant and trusted product content to drive seamless customer experience

Increase Supply Chain and Inventory Management Efficiencies: According to a McKinsey consumer study published in December when faced with out of stocks, 71% of consumers will switch brands and retailers. IDMC for Retail helps improve inventory visibility at the store and distribution center level and increases the accuracy of demand forecasting. In a world where climate change and geopolitical tensions, will continue to create supply chain uncertainty, closer collaboration with suppliers is a powerful way to address supply disruption and price volatility.

IDMC for Retail helps:
• Boost productivity and cut costs by reducing business overhead and manual work for managing supplier information
• Shrink supplier and product onboarding and qualification time from weeks to days
• Improve supplier collaboration, assess compliance and manage supplier risk to build a resilient and sustainable supply chain

Maintain Customer Trust and Loyalty with Industry-Certified Data Governance and Compliance Standards: Data privacy regulations directly impact the way multinational companies conduct their business. IDMC for Retail helps prevent exposure and reduces risk by providing effective data governance and privacy capabilities. By providing visibility into data usage and access, it reduces risk exposure to potential breaches and non-compliances with data privacy laws such as GDPR and CCPA, reduce financial penalties, and help build trust and loyalty from customers.

IDMC for Retail helps:
• Rapidly find and compile personal data, which is held in countless disconnected systems throughout your enterprise
• Respond to subject requests and data breaches within the timelines required by GDPR, CCPA and other regulations
• Foster IT and business collaboration, driving productivity and rapidly accelerated reporting processes

Informatica has a rich ecosystem of cloud partners, AWS, Google Cloud, Microsoft, Snowflake and Databricks to provide seamless integrations to help retail customers succeed in their cloud-first digital transformation. GSI partners like Accenture, CapGemini, Deloitte, Cognizant and Wipro have been integral to Informatica’s cloud expansion in the retail industry and actively engaged in helping several joint retail customers in adopting IDMC.

“The Informatica Intelligent Data Management Cloud for Retail is the only, end-to-end, cloud-neutral data management platform built to enable retail organisations continuously innovate their customer experience, omni-channel shopping and supply chain efficiencies with seamless access to trusted data when and where they need it,” said Jitesh Ghai, Chief Product Officer, Informatica. “The retail industry is on an accelerated path to digital transformation in the next few years and Informatica is helping retail organisations stay competitive and drive business value by unlocking the value of unified data.”

Want to learn more about cloud and cyber security from industry leaders? Check out Cyber Security & Cloud Expo. The next events in the series will be held in Santa Clara on 11-12 May 2022, Amsterdam on 20-21 September 2022, and London on 1-2 December 2022. 

Explore other upcoming enterprise technology events and webinars powered by TechForge here.


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How is Machine Learning Affecting Advertising and Marketing?



How is Machine Learning Affecting Advertising and Marketing?

Machine learning is transforming advertising and marketing by segmenting and targeting specific audiences with relevant messages.

The use of machine learning in marketing parallels that of its use in news media. Publishers as varied as the Washington Post & Reuters and even smaller publishers regularly use machine learning tools to produce copy around financial and sports results, leaving journalists more time to get on with analysis that really adds value to their consumers.


Source: Smarty Ads

Advertisers and marketers can use machine learning to create more personalized experiences, target the right audience, reduce costs, and make faster decisions. 

1. Advanced Customer Profiling


Source: Datafloq

Knowing your target audience and understanding their needs, interests, and preferences is essential for the success of your digital marketing efforts.

Having an accurately defined ideal customer profile and buyer personas lets you segment your email and content marketing and personalise your marketing messaging and content.

In advertising, as in other industries, machine learning is focused on using algorithms to ‘mimic’ human intelligence by programming them to think and respond in the same way humans do.

AI-powered chatbots are changing the customer support landscape tremendously. 

As an example, Alexa is using machine learning to make predictions on its own about what your words mean, how to respond to them, and what action you’re requesting.

Alexa is not being programmed explicitly to get better after each user’s query. Instead, Alexa is using data from each interaction with users to improve its interactions with the next one.

2. Increasing Loyalty & Retention

It’s crucial to offer your prospects answers to any questions they might have regarding your product or services as that can be a make-or-break factor to purchase. Similarly, once they decide to opt for your product, they’d like to start using it right away. Meaning they’ll be frustrated if they don’t understand how a certain feature works.

Effective machine learning solutions provide marketers with a central platform for managing large amounts of data. These platforms can derive insightful marketing intelligence about your target audience making it easier to make data-driven decisions.

Machine learning technology can help to create more effective, insightful and target consumer-specific ads and campaigns through big data marketing. Data collected from keyword searches, general online activity and social media profiles can be utilized to develop a smarter marketing strategy.

3. Saving Costs with Dynamic Pricing

As machine learning is able to quickly process data, it can save a lot of time when prospecting–shortening the sales funnel. The ability to adapt to the user’s behavior and store and interpret large amounts of data saves marketers a ton of time and effort compared to doing research manually.

Machine learning can be used to set the price of products dynamically depending on demand, availability, customer profiles, and other factors to maximize both sales and profits.

If you’ve ever searched for a flight and then gone back to buy it a couple of days later only to find it’s gone up a few hundred dollars, this is also a good example of dynamic pricing at work.

4. Better SEO & PPC with Micro-Segmentation


Source: Datafloq

Machine learning helps businesses expedite the process and enhance the accuracy of keyword research, SEO, PPC, competitor analysis, search intent research, and more.

SEO and PPC as being two sides of the same coin: search. The most obvious benefit of combining SEO and PPC efforts is added exposure on the search engine results pages (SERPs).

Machine learning divides a large, diverse group into smaller segments with similar needs, wants, and preferences. This allows companies to target customers with personalized keywords, messaging and offers.

With machine learning micro-segmentation technology, businesses can send highly relevant messages to their audience based on their specific interests and needs. This increases response rates significantly and helps you build stronger relationships with customers over time.

5. Predicting Future Trends

Predicting the future has always been a crapshoot for organizations. That’s why marketing and advertising budgets are often so large: Organizations are hedging their bets and throwing a lot of resources at the problem of figuring out what consumers want next. If a company can accurately predict people’s wants and needs, it can create products that will be highly successful, and that means more money for everyone involved.

Machine learning is taking over this role of predicting the future and doing a better job than humans. When companies use machine learning, they can analyze massive amounts of data much faster than anyone. Predictive algorithms give marketers and advertisers insights into what’s coming next based on trends they see in the market. They can make informed decisions about their marketing campaigns now that they’ve been given a crystal ball into the future.


By embracing machine learning incorporating it into your digital marketing and advertising strategy, you can target your consumer audience with much more precision, and engage your audience more effectively. 

Machine learning allows advertisers and marketers to identify target customers, curate marketing content, create marketing strategies and regulate dynamic pricing based on customer behavioral patterns

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