TECHNOLOGY

How is Machine Learning Affecting Advertising and Marketing?

Published

2 years ago

November 29, 2022

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.

Conclusion

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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TECHNOLOGY

Next-gen chips, Amazon Q, and speedy S3

Published

10 months ago

December 1, 2023

Max

AWS re:Invent, which has been taking place from November 27 and runs to December 1, has had its usual plethora of announcements: a total of 21 at time of print.

Perhaps not surprisingly, given the huge potential impact of generative AI – ChatGPT officially turns one year old today – a lot of focus has been on the AI side for AWS’ announcements, including a major partnership inked with NVIDIA across infrastructure, software, and services.

Yet there has been plenty more announced at the Las Vegas jamboree besides. Here, CloudTech rounds up the best of the rest:

Next-generation chips

This was the other major AI-focused announcement at re:Invent: the launch of two new chips, AWS Graviton4 and AWS Trainium2, for training and running AI and machine learning (ML) models, among other customer workloads. Graviton4 shapes up against its predecessor with 30% better compute performance, 50% more cores and 75% more memory bandwidth, while Trainium2 delivers up to four times faster training than before and will be able to be deployed in EC2 UltraClusters of up to 100,000 chips.

The EC2 UltraClusters are designed to ‘deliver the highest performance, most energy efficient AI model training infrastructure in the cloud’, as AWS puts it. With it, customers will be able to train large language models in ‘a fraction of the time’, as well as double energy efficiency.

As ever, AWS offers customers who are already utilising these tools. Databricks, Epic and SAP are among the companies cited as using the new AWS-designed chips.

Zero-ETL integrations

AWS announced new Amazon Aurora PostgreSQL, Amazon DynamoDB, and Amazon Relational Database Services (Amazon RDS) for MySQL integrations with Amazon Redshift, AWS’ cloud data warehouse. The zero-ETL integrations – eliminating the need to build ETL (extract, transform, load) data pipelines – make it easier to connect and analyse transactional data across various relational and non-relational databases in Amazon Redshift.

A simple example of how zero-ETL functions can be seen is in a hypothetical company which stores transactional data – time of transaction, items bought, where the transaction occurred – in a relational database, but use another analytics tool to analyse data in a non-relational database. To connect it all up, companies would previously have to construct ETL data pipelines which are a time and money sink.

The latest integrations “build on AWS’s zero-ETL foundation… so customers can quickly and easily connect all of their data, no matter where it lives,” the company said.

Amazon S3 Express One Zone

AWS announced the general availability of Amazon S3 Express One Zone, a new storage class purpose-built for customers’ most frequently-accessed data. Data access speed is up to 10 times faster and request costs up to 50% lower than standard S3. Companies can also opt to collocate their Amazon S3 Express One Zone data in the same availability zone as their compute resources.

Companies and partners who are using Amazon S3 Express One Zone include ChaosSearch, Cloudera, and Pinterest.

Amazon Q

A new product, and an interesting pivot, again with generative AI at its core. Amazon Q was announced as a ‘new type of generative AI-powered assistant’ which can be tailored to a customer’s business. “Customers can get fast, relevant answers to pressing questions, generate content, and take actions – all informed by a customer’s information repositories, code, and enterprise systems,” AWS added. The service also can assist companies building on AWS, as well as companies using AWS applications for business intelligence, contact centres, and supply chain management.

Customers cited as early adopters include Accenture, BMW and Wunderkind.

Want to learn more about cybersecurity and the cloud from industry leaders? Check out Cyber Security & Cloud Expo taking place in Amsterdam, California, and London. Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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TECHNOLOGY

HCLTech and Cisco create collaborative hybrid workplaces

Published

10 months ago

November 29, 2023

Max

Digital comms specialist Cisco and global tech firm HCLTech have teamed up to launch Meeting-Rooms-as-a-Service (MRaaS).

Available on a subscription model, this solution modernises legacy meeting rooms and enables users to join meetings from any meeting solution provider using Webex devices.

The MRaaS solution helps enterprises simplify the design, implementation and maintenance of integrated meeting rooms, enabling seamless collaboration for their globally distributed hybrid workforces.

Rakshit Ghura, senior VP and Global head of digital workplace services, HCLTech, said: “MRaaS combines our consulting and managed services expertise with Cisco’s proficiency in Webex devices to change the way employees conceptualise, organise and interact in a collaborative environment for a modern hybrid work model.

“The common vision of our partnership is to elevate the collaboration experience at work and drive productivity through modern meeting rooms.”

Alexandra Zagury, VP of partner managed and as-a-Service Sales at Cisco, said: “Our partnership with HCLTech helps our clients transform their offices through cost-effective managed services that support the ongoing evolution of workspaces.

“As we reimagine the modern office, we are making it easier to support collaboration and productivity among workers, whether they are in the office or elsewhere.”

Cisco’s Webex collaboration devices harness the power of artificial intelligence to offer intuitive, seamless collaboration experiences, enabling meeting rooms with smart features such as meeting zones, intelligent people framing, optimised attendee audio and background noise removal, among others.

Tags: Cisco, collaboration, HCLTech, Hybrid, meetings

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TECHNOLOGY

Canonical releases low-touch private cloud MicroCloud

Published

10 months ago

November 28, 2023

Max

Canonical has announced the general availability of MicroCloud, a low-touch, open source cloud solution. MicroCloud is part of Canonical’s growing cloud infrastructure portfolio.

It is purpose-built for scalable clusters and edge deployments for all types of enterprises. It is designed with simplicity, security and automation in mind, minimising the time and effort to both deploy and maintain it. Conveniently, enterprise support for MicroCloud is offered as part of Canonical’s Ubuntu Pro subscription, with several support tiers available, and priced per node.

MicroClouds are optimised for repeatable and reliable remote deployments. A single command initiates the orchestration and clustering of various components with minimal involvement by the user, resulting in a fully functional cloud within minutes. This simplified deployment process significantly reduces the barrier to entry, putting a production-grade cloud at everyone’s fingertips.

Juan Manuel Ventura, head of architectures & technologies at Spindox, said: “Cloud computing is not only about technology, it’s the beating heart of any modern industrial transformation, driving agility and innovation. Our mission is to provide our customers with the most effective ways to innovate and bring value; having a complexity-free cloud infrastructure is one important piece of that puzzle. With MicroCloud, the focus shifts away from struggling with cloud operations to solving real business challenges” says

In addition to seamless deployment, MicroCloud prioritises security and ease of maintenance. All MicroCloud components are built with strict confinement for increased security, with over-the-air transactional updates that preserve data and roll back on errors automatically. Upgrades to newer versions are handled automatically and without downtime, with the mechanisms to hold or schedule them as needed.

With this approach, MicroCloud caters to both on-premise clouds but also edge deployments at remote locations, allowing organisations to use the same infrastructure primitives and services wherever they are needed. It is suitable for business-in-branch office locations or industrial use inside a factory, as well as distributed locations where the focus is on replicability and unattended operations.

Cedric Gegout, VP of product at Canonical, said: “As data becomes more distributed, the infrastructure has to follow. Cloud computing is now distributed, spanning across data centres, far and near edge computing appliances. MicroCloud is our answer to that.

“By packaging known infrastructure primitives in a portable and unattended way, we are delivering a simpler, more prescriptive cloud experience that makes zero-ops a reality for many Industries.“

MicroCloud’s lightweight architecture makes it usable on both commodity and high-end hardware, with several ways to further reduce its footprint depending on your workload needs. In addition to the standard Ubuntu Server or Desktop, MicroClouds can be run on Ubuntu Core – a lightweight OS optimised for the edge. With Ubuntu Core, MicroClouds are a perfect solution for far-edge locations with limited computing capabilities. Users can choose to run their workloads using Kubernetes or via system containers. System containers based on LXD behave similarly to traditional VMs but consume fewer resources while providing bare-metal performance.

Coupled with Canonical’s Ubuntu Pro + Support subscription, MicroCloud users can benefit from an enterprise-grade open source cloud solution that is fully supported and with better economics. An Ubuntu Pro subscription offers security maintenance for the broadest collection of open-source software available from a single vendor today. It covers over 30k packages with a consistent security maintenance commitment, and additional features such as kernel livepatch, systems management at scale, certified compliance and hardening profiles enabling easy adoption for enterprises. With per-node pricing and no hidden fees, customers can rest assured that their environment is secure and supported without the expensive price tag typically associated with cloud solutions.

Tags: automation, Canonical, MicroCloud, private cloud

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