What’s the one essential all B2B landing pages need to be high-converting? The advice of “don’t sell the drill, sell the hole” isn’t always true. There is a different approach for talking to a carpenter who already owns an array of drills, compared to a homeowner who hasn’t considered the need for a hole.
That’s the reason to aim a landing page at the right buying quadrant.
Every page already aims at one of these without even realizing it (or in the worst cases, tries to talk to two). Taking a step back to refocus the copy and imagery is a key step that’s usually missed. Here are the four buying quadrants:
Hint: To be aiming at enterprises, they’re probably in the top right
Eager 1st-time buyers – Most companies usually fit this group by default. The page will talk about all the joys of adopting this kind of service. A typical example is a marketing agency describing the benefits of PPC as if the prospect hasn’t considered it before.
Actively looking to switch – If the target audience is bigger companies, the page should probably address the headaches they’re having with their current solution. With the marketing agency example, the page would now be more about how they will avoid the issues that prospects have probably come up against with other agencies or freelancers.
Have not considered solutions before – This is the least common in the B2B space, to the point where caution is advised while choosing it. You may not want to admit it, but you’re probably competing with an existing solution such as Excel.
Happily using current solution – This doesn’t just mean a competing product. It could be tracking a process in Excel, organizing something with pen and paper, or just getting an intern to do it.
The key is to frame why your offer is worth the uncertainty of changing from their current way of doing things. Have a think about your ideal prospects and which of these quadrants they fit in, then check your landing pages to see if they are relevant or if they are talking to a different type of prospect.
2. Deciding on Your Audience and Pain Points
What steps should a B2B go through when deciding on the audience and pain point(s) to optimize a landing page for? How should a business apply these audience findings?
First, think about the traffic source. It is possible that a page’s visitors from different sources fit into different buying quadrants, so think through which one the current landing page is for.
For example, search traffic from high-intent keywords might be actively looking to switch, while visitors to a general blog post could be happily using their current solution. That means they will require completely different sales points.
If you are writing for a low-intent audience, then it is important to think through whether they’re even aware of the problem or if they’re blissfully ignorant.
Let’s say they’re currently using an open source software to handle a task. They might not realize how much easier things would be if they used a premium product with robust integrations, and the amount of work this would save them. So, start by planning out how you’ll take them through those decision stages, with the questions they might be asking themselves and the relevant info to lead them to your point of view.
3. Other Research for Landing Page Optimization
What other research should a brand conduct before optimizing a landing page?
A go-to answer is to talk to the sales team. Ideally, listen to some of the sales calls with actual prospects. Heat maps might look pretty, but they won’t have the same depth of insight as actual humans who have spent hours talking to the prospects.
It is recommended having a sit down with a member of the sales team to discuss questions such as:
How are prospects dealing with the issue before they look at us?
Is there a typical sparking incident that makes solving it a priority?
What are their biggest objections you need to address before they’ll buy?
Why do they pick us over competitors and other solutions?
This conversation can turn up so many gems and ideas for how to improve the page. Be sure to gently nudge for details at any stage instead of accepting broad answers.
4. Selecting The Best Lead Magnet
How can a brand make sure they select the best lead magnet to advertise on a landing page? Think about the journey that your prospects are on and what headaches they are dealing with. The lead magnet should be suited to what they’re dealing with, especially in terms of how advanced the content is.
A marketing agency, with their Beginner’s Guide to SEO, isn’t going to appeal to the CMOs that they want to attract. Instead, they can do so by creating lead magnets about topics relevant to veteran marketers, such as proving long-term ROI and integrating with Salesforce.
Part of it is about accepting that an ideal lead magnet might bring in fewer leads than a broad one. But, those leads should be of higher quality.
5. The Biggest Learning in Landing Page Optimization
So much effort is often put into the design. Days are spent building out clever parallax scrolling or playing with whitespace.
Yet, so long as the design looks vaguely attractive and easy to look through…changing it doesn’t seem to matter.
It is common to hear companies come and say that they have tried redesigning the page several times, but it hasn’t improved the performance. Then, once you overhaul the copy and images, their conversion rates finally go up.
It is easy to understand why design is prioritized. It’s more obviously difficult than writing copy, and fast-moving trends mean a page can quickly look dated.
But unfortunately, it is important to learn that a redesign might bring small lifts, but won’t fix a struggling page.
6. Landing Page Copywriting Vs. Other Copywriting
What makes landing page copywriting different from copywriting for other web pages?
Landing pages should be highly targeted in who they’re talking to and the funnel step they’re aimed at. Homepages, on the other hand, are a different challenge. While they are also an entrance page, they have to be more multi-purpose in who they’re talking to. If you serve different industries or company sizes, then the homepage will be watered down by having to be relevant to all of them.
Think of them more as a starting point and guide them to the content that is most relevant for them. It can be links to specific features or industry pages, but the key is to get them discovering the details that will move them closer to becoming buyers.
7. Concisely Covering Key Points That Will Lead to Conversions
How can a brand make sure it covers the points that would best convince a prospect to convert, without making a landing page text-heavy?
As a priority, make your subheadings almost able to stand alone. A visitor should be able to skim down the subheadings and get a sense of what you do and who you’re for without reading any of the body copy.
It might mean swapping questions like “Who is it for?” with the equivalent answer such as “Designed for enterprise”. Next, think of the body copy in each section as reinforcing the subheading. It should give proof or details to reinforce the claim, such as what about you makes you suitable for enterprise.
It can be tempting to squeeze in semi-relevant details that you want to be on the page somewhere, but that will dilute the impact of that paragraph and make it harder to read. In truth, I think the issue is usually that the copy is hard to digest and not that the word count is too high, so stirring together different sales points into one section is a quick way to confuse things.
8. Avoiding Landing Page Optimization Mistakes
What are the biggest mistakes people tend to make when optimizing landing pages for their business? How can they avoid these mistakes?
You can try rewording things, but if you’re still trying to sell bacon to a vegetarian, then it’s not going to work. The industry advice is to test one change at a time, which is usually interpreted as changing one small detail.
I see lots of A/B tests where they have tested a different way of saying the same thing. Maybe they focus the headline on a different selling point, but it is still generally aimed at the same audience facing the same problems.
If your conversion rate is already decent and you’re only looking for small improvements, then that’s ok. But if your campaign is struggling, then you’ll need to test a double-or-nothing style overhaul.
An overhaul can still be a test of a single hypothesis. It can test an idea such as, “would a landing page aimed at open source users perform better?” Every element might need to change, but all in support of that one idea.
So, don’t be scared to think big in your split tests, as big lifts in your optimization will only come from testing big changes.
9. Using Complementary Images On Your B2B Landing Page
As a final tip, plan out how each image can build on the corresponding subheading. Very often one can see things like dashboard screenshots that have nothing to do with the text alongside them.
The pictures shouldn’t just be there to stop the page from being too text-heavy. They should be working with the sales material. If you’ve written “set it up in a few clicks,” then illustrate what those clicks are, instead of showing a shot of the UI.
How AR and AI Work Together to Build Unique Mobile Experiences?
The intriguing partnership of Augmented Reality (AR) and Artificial Intelligence (AI) is a match made in the digital heaven. An AR application can become more beneficial when AI is incorporated into it. The natural bridging of AR and AI enables mobile app developers to build more interactive and intriguing apps. This article explores a few practical ways in which AR and AI can be combined to build incredible mobile experiences.
Ways AI and AR Complement Each Other
The partnership between AR and AI is likely to have a profound impact on customer experience. Companies are developing next-generation applications for mobiles that employ AR and AI technologies. In fact, AI is the heart of practically all AR platforms.
Though Artificial Intelligence and Augmented Reality have distinct technologies, they can sync with one another on a variety of applications. They can leverage each other’s best features and aspects to build innovative mobile experiences. AI enables AR to have a multidimensional interaction with the physical environment. It allows you to manipulate 2D and 3D virtual objects with your words, eyes, and hands.
It is anticipated that the demand for AR-based apps is bound to soar in the next four to five years. Hence, the search for appropriate Software Development Kits (SDK) and Application Program Interfaces (API) for AI and AR is ongoing.
Current State of SDKs and APIs for AR and AI
As the capabilities of current SDKs (Software Development Kits) and APIs (Application Programming Interfaces) rapidly expand, the number of commercial opportunities increase exponentially. Consider a few examples:
Vuforia: This is an Augmented Reality SDK that enables app developers to build mobile-centric, immersive AR experiences. It is capable of supporting both iOS and Android devices, allowing brands to develop apps with minimal commercial and technical risks.
ARCore: This is Google’s proprietary AR SDK. It enables developers to get their AR apps up and running on mobile devices. ARCore supports iOS devices and allows developers to build rich and immersive AR experiences supported by mobile devices.
Core ML: This is a Machine Learning framework used across multiple Apple devices. This API allows you to perform real-time predictions of live images on your device. Its low latency and near real-time results are its biggest advantages. Core ML is an application that can be run without network connections.
TensorFlow Lite: This is an open-source deep learning framework focused on mobile device inference. TensorFlow Lite enables developers to insert their own custom models.
Practical Ways to Combine AR and AI
The marriage of AR and AI opens up endless opportunities. Here are a few ways in which this combination is deployed to create digital miracles.
1. Speech Recognition: As an AI model listens to what you say, AR effects appear in front of you. An example would be when you say ‘pizza,’ a virtual pizza slice appears in front of your mouth on the app screen.
2. Image Recognition and Image Tracking: It allows customers to see how an object would look and fit in a given space. Combining AR with AI technology allows users to move still photos of items into a still image of a room and assists them in making a decision. Example: the popular IKEA Place.
3. Human Pose Estimation: It is a technique that detects human figures and poses. It predicts the positions of a person’s joints in an image or video. This can be used in controlling AR content. Yopuppet.com is one example.
4. Education: It allows students to gain new perspectives by interacting with virtual reality. For example, they can visualize and interact with a 3D life-size version of the human body.
5. Recognizing and Labelling: When the camera is pointed to a scene or an image, the AR app displays a label that indicates the object or the item when it recognizes it.
6. Car Recognition: Using a smartphone camera, this tech-application allows its customers to sit inside the car and explore the car’s interiors. There isn’t even a need to download the application.
7. Object Detection: AR-AI combination can be applied to automatically learn and detect the position and extent of the objects within an image or a video. This mobile-friendly model facilitates interaction between physical and digital objects.
The bridging of AR and AI is offering businesses an opportunity to empower their customers with ways to sharing information in captivating ways. Together, AR and AI continue to enhance mobile experiences, enabling developers to design richer, more intuitive, and relevant experiences for their diverse consumers in numerous ways.
2020 forever changed the trajectory of digital transformation in every business, in every industry. As the global pandemic endured, customers prioritized their health and safety, and embraced digital-first shopping behaviours. With every consumer click, tap, and swipe, businesses were forced to advance their experience.
Innovators, however, must look beyond digitization, basic ecommerce, and ordinary digital engagement, to differentiate, and create sought after value. Augmented reality, and mixed reality overall, represents a unique accelerant to deliver new experiences, awaken the senses, online and IRL (in real life), and enhance engagement throughout the customer’s journey. Augmented reality represents an immediate opportunity to enrich shopping experiences.
AR for an Enhanced Experience
With AR, brands have a novel opportunity to deliver value-added experiences, beyond shiny object syndrome. Through augmented reality, brands and retailers can unlock a new dimension to digital and physical shopping where products and experiences are brought to life. These experiences can come to life at home, in-store, or anywhere. All it takes is imagination and innovation.
A recent study found that 63% of consumers believe AR will transform their shopping experience and 61% indicated that they would prefer to make purchases on sites that offer AR technology. More so, 70% of consumers reported that they would be more loyal to brands incorporating AR as part of their shopping experience.
The stores as we know are changing with AR. These will allow customers to engage in ways unknown and help retailers generate leads in better and optimized ways. This includes revamped trail rooms, trial rides for cars and more. You could even share them over with your friends with just one tap!
AR in Ecommerce Today
IKEA paved the way for AR commerce by helping customers move beyond imagining what furniture could look like in their spaces. Launched in 2017, the IKEA Place app helps customers visualize products from its catalogue, through AR, at true scale, within any space.
Following the popularity of the IKEAs AR app, a handful of innovative brands have continued to demonstrate the promise of AR in online and in-store shopping.
For example, Nike brought AR to the footwear and clothing categories. The experience uses AR to scan the customers’ feet and find the right shoe for them. From scanning your feet to finding the perfect size, the process takes less than one minute.
Warby Parker is innovating the way customers try on glasses with their at-home try-on AR experience through their mobile app. When a customer enters the “try on” area of the app, they simply flip their phone to selfie mode and select the frames they want to see on their face. While other glasses brands have tried AR, Warby Parker has paved the way with a real-time selection of frames.
Walmart is using AR to interact with their customers on their shelves through a range of display options of hair colour and recommended shades that customers can try on in real-time. Once a user scans the barcode provided, their camera opens to try on all options. Walmart is the first retailer to implement brick-and-mortar AR for their stores to enhance in-store experiences.
AR also is getting a big boost from one of the most revered, market-making innovators in the game. In 2020, Apple entered the mix, mixed reality that is, with the integration of LiDAR scanners in higher-end iPhone and iPad models. These new cameras will give consumers the ability to scan and also virtually imprint vivid 3D images into online and real-world experiences. Apple also launched what it refers to as the “world’s largest AR platform,” giving developers the tools they need to develop and market compelling AR experiences. AR doesn’t just mean augmented visualization. The company also introduced spatial audio capabilities in its most recent AirPods Pro and Max lines, which sets the stage for immersive, integrated audio and video virtual experiences.
Even in the early days of COVID-19, the market size for AR was estimated at almost $19 billion by 2023. With the pandemic lingering, consumer adoption of ecommerce and online shopping will only continue to gain momentum. This definitely is AR’s moment.
Retailers and brands must think beyond traditional retail, commerce, and even legacy spatial design. Innovators must reimagine customer engagement and CX through a lens of next-generation experience architecture, one that augments, enhances, and blurs the line between physical and digital (#PhyDi) worlds.
AR represents an opportunity for experience architects to imagine and enliven innovative, value-added, and engaging new worlds. Amazing, productive AR experiences represent a competitive advantage and a promise to drive growth by increasing customer engagement, attracting new shoppers, and boosting conversion rates.
Whether you are already an experienced developer or just starting out, if you want to become really good in this industry, you need to constantly sharpen your skills to stay relevant. Here are some of the most valuable developer skills to tackle this year.
Of course, you won’t need all of them and this list isn’t complete. But it should give you a good idea of what to learn next or what to improve on.
1. Practice Coding Every Day
Even if it’s for only 30 minutes. This will help you learn the best development practices and grow your skills. It will also help you stay in top form and master new technologies.
2. Learn To Be A Good Communicator (Both While Writing And Speaking)
You don’t need to speak English like a native speaker, but you do need good enough communication skills to help clients understand what you are saying. Whether it’s in meetings, emails, or even on the phone, you don’t want to lose a client because they couldn’t understand your words. Also, good speaking and writing skills help make you stand out from other developers.
3. Practice Object-Oriented Design Principles
Even if you just started programming, learning OOP will give you many benefits over time. It will also make it much easier for you to read other people’s code, which is essential when working with other developers and your team members.
4. Learn How To Use Version Control Systems (e.g. Git) Effectively
Version control systems are essential for any developer who works on multiple projects simultaneously or collaborates with other developers on projects.
5. Improve Your Problem-Solving Skills
Software development is a complex field. You’ll be exposed to many different problems and tasks during your career. Make sure you can solve them effectively by learning how to think like a developer.
6. Learn How To Use Design Tools Such As Photoshop, Sketch, And Illustrator
Good-looking websites and apps are essential if you want to create high-quality products that users love. While it’s possible to learn how to design using tutorials and YouTube videos, most of the time, you will need some formal training in this area when you start working on real projects.
7. Keep Learning New Technologies And Languages
Don’t get stuck on one stack! Learning new languages and frameworks will help you stay employable in this industry. If you have had the same stack for a long time, then there is a good chance that your skills will become obsolete over time. Always try to stay up to date with the newest technologies used by top developers around the world.
8. Learn At Least One Scripting Language (e.g. Python)
Scripting languages are useful for automating repetitive tasks. Even if you don’t want to become a full-time developer, scripting can make your life easier as a software engineer.
9. Learn How To Write Clean And Maintainable Code
You will have to spend lots of time reading other people’s code. If the code is not clean, then it will be very hard for you to understand what’s going on. So you must write clean and readable code yourself.
One way to improve your coding skills is by writing unit tests (e.g. by using JUnit). This will help you catch bugs early in the development process. Also, try to keep your methods short so it will be easier to read them later when you need to come back and fix something in the project that you wrote months ago.
10. Learn To Think Ahead And Plan Out How A Feature Should Work Before You Start Developing It
It takes time to go from writing an initial idea for a feature/product/bug fix to having that feature ready on the market. You need to be able to think ahead and make sure that everything fits together properly during this whole process (and also after). This includes planning with your team members, asking users what they want, talking with stakeholders about their requirements, etc. Don’t just start coding things without thinking first!
11. Learn How To Implement Security Measures Properly
There is a lot of information out there about security, and it’s easy to get confused and overwhelmed. Make sure that you go beyond the obvious like ‘make sure your password is strong enough’ and learn more about security threats and how to fix them.
12. Don’t Be Afraid To Ask Questions
Asking questions is a great way to learn. One of the biggest mistakes you can make is to assume that you know everything. Many developers tend to think that asking for help is a sign of weakness, but it’s actually a sign of strength. If you don’t understand something, ask someone who does and then try to figure it out yourself as well. This will help you gain a deeper understanding of the topic in question.
13. Learn How To Work With Different Environments (Mac, Linux, Windows)
You don’t have to become an expert in all platforms, but you should know how they work and what their pros and cons are. Also, knowing how different development environments work will allow you to save time when switching between them. For example, developing an Android app on Windows or Mac will force you to change your workflow since the process is quite different from using Linux or Ubuntu.
14. Practice Pair Programming Regularly With Your Team Members (or Others)
Pair programming means two people working together on one computer at the same time — one person sitting behind the keyboard writing code while the other person observes and gives feedback/suggestions/code reviews, etc.
Pair programming has many benefits, including a better understanding of the problem domain, sharing knowledge and ideas between team members, faster debugging, etc. It also allows developers to get comfortable with each other through regular communication and helps team members build trust towards each other, which greatly improves teamwork.
15. Understand Design Patterns (SOLID Principles And Object-Oriented Design Patterns)
You don’t have to know every single pattern by heart, but understanding what they are will help you a lot as a software developer. Object-oriented design patterns are used repeatedly in different frameworks and technologies, so understanding them will be extremely useful for your job as a software developer.
The SOLID principles guide us when writing code:
Liskov substitution principle
Interface segregation principle
Dependency inversion principle
16. Learn How To Deal With Change As A Software Developer
When working on new projects or even when working with existing code base, things change from time to time (and not always because we want them to). You need to constantly adapt to these changes if you’re going to continue being productive in this business. If you cannot handle change well, you will eventually get stuck with outdated skills that won’t help you much anymore.
17. Learn How To Put Yourself In Other People’s Shoes
This is a beneficial skill in the software development industry. You need to learn how to see things through your client’s eyes and try to understand what they want or need. You need to communicate with them and make sure you deliver what they want.
18. Learn About Business Processes And Soft Skills
It doesn’t matter if you work for yourself or for another company. You must understand business processes and soft skills like communication, time management, problem-solving, and more. These are all crucial skills that will make you stand out from other developers who don’t know anything about this stuff.
19. Learn How To Deal With Deadlines
Everybody knows that projects sometimes run late and deadlines are not met. As a developer, you need to learn how to meet deadlines by setting smaller checkpoints in your projects that you can check off as you go. This will help you be more efficient and get the job done on time.
20. Learn How To Learn New Technologies Fast
As mentioned before, developers need to stay relevant and learn new technologies quickly. This means learning new languages and learning about new frameworks or libraries that can help you solve problems more efficiently. It’s not only important that you know about the technology but also why it’s better than the others.
If you don’t understand something or there is something that isn’t clear to you, ask questions! Don’t be afraid of looking stupid because if someone doesn’t understand something, they will never fully master it!
Though hiring a PPC expert may not sound like a big deal, it is quite a daunting task to find that one expert who can actively manage your Pay Per Click campaigns in the real world. This is crucial because hiring the wrong person can have adverse effects. Reports suggest that 97% of the ad campaigns fail due to inadequate quality of tracking and businesses lose a lot of money investing in the wrong keywords.
Therefore, while hiring PPC experts might not be an easy job; here are some aspects to stay on the look-out for:
1. Shortlisting Potential Experts
Everyone in the market will claim to the best PPC expert. However, you can easily check their claims and shortlist the ones that fit your bill and satisfy your needs. Do not trust your shortlisted PPC experts blindly! There will be more than what meets the eye.
When choosing a PPC expert, list out your expectations and see which ones align perfectly with your plan. Expensive PPC experts do not guarantee results. Also, PPC experts new to the market will be ready to experiment and try dynamic methods to bring results. Therefore, find the one with a healthy balance between experience and working dynamics.
2. Working Methodology
When it comes to quality, you should not be compromising at all. Here’s where you learn your agency’s working methodology in detail and how they maintain their standards when managing a PPC campaign.
Since every project is different, the strategies for every campaign will be different and unique too. Therefore, be sure to ask about the agency’s quality assurance measures when the Google Ads account is set up. Also, make sure adequate resources are allocated for critical tasks like client communication, campaign optimisation, and development, etc.
If your PPC expert is avoiding answering your questions about maintenance and utilisation, wake up and walk right out of it. You have every right to access this information and agencies are obliged to stay as transparent as possible with the details that they share with you.
As a client, you will have access to each ad account and learn about its progress and cost. For a PPC expert to work like a well-oiled machine, there should be weekly communications related to the campaign instead of a monthly report. Getting the data out in real-time is the key to maintaining transparency between the PPC experts and the client.
PPC campaign boostings are never constant. It is more important than ever to prevent malpractices like inserting random dynamic keywords or making use of bad headlines and bad ad copies. Such stringent rules are to be strictly followed to avoid penalties for the client and the PPC expert.
Apart from reviewing and launching campaigns, a PPC expert should evolve according to the nature of the business. They should have a bespoke, long-term plan ready for the business and keep implementing changes as the need arises to maintain an edge over the competitors.
Hiring a PPC expert is no child’s play. Keeping the above-mentioned points in check and you should be able to hire the best PPC expert and get the most out of your PPC campaign. With NeoSOFT, hire a PPC expert who strives to provide personalised services and upholds your business goals throughout the term.
Decades ago, the idea of embedding sensors and chips into physical objects would sound insane and impossible. Today, Internet of Things has drastically transformed most aspects of our everyday life such as driving, cooking, purchasing, etc. The number of IoT units in different industries is projected to amount to 30.9 billion units worldwide by 2025.
The manufacturing industry is also seeing a rapid rise in the deploying of IoT. Many plants have already incorporated connected control systems for their operation and supervision. The primary benefits of IoT solutions include:
Helping to detect and avoid issues that may cause delays.
Increasing production quality of an industrial unit and reap benefits from raw stuff, and manufactured components using cognitive operations.
Enabling the managers for better allocating resources, improving worker skillfulness and making the work environment safe.
Currently, IoT is popularly harnessed to help deal with facility and asset management, security and operations, logistics, customer servicing, etc., making it a highly promising trend in the manufacturing sector.
Here are some of the best IoT use cases in manufacturing —
1. Predictive Repairing
By connecting IoT-driven gadgets with different sensor points (temperatures, vibration, voltages, currents, etc.) to other devices, IFTTT, cloud/API or legacy systems manufacturers can obtain essential maintenance data. This kind of information allows them to estimate the current condition of machinery, determine warning signs, transmit alerts, and activate corresponding repair processes.
This transforms maintenance into a fast-paced and automated practice, which foresees a failure well in advance. Moreover, this kind of predictive repairing saves cost exponentially compared to the traditional preventive measures since the actions are taken exactly when they are necessary.
By getting valid data on time, managers can detect issues and plan maintenance operations. This helps in prolonging equipment lifetime, contributing to plant safety, and lowering the risks of accidents that affect the environment negatively.
2. Remote Production Control
Reallocating your company’s computational resources to a custom cloud or connecting the device to one of the popular BaaS (backend as a service) or PaaS (platform as a service) cloud computing models, you can collect and analyze large-scale data sets necessary for supervising various field devices like switches, valves, and other indication elements.
Thanks to IoT, this data can be transmitted to the industrial automation system which then ensures an overall control of machinery amidst the production process.
Telecommunications, oil and gas industries, as well as power generation, have all been already reaping the benefits from IoT devices implanted into distant control systems.
The most prominent feature of remote production control in the industrial automation system is the centralized supervision over the machinery in the process of production. Information obtained through distant control provides a much clearer and faster insight into the actual production field.
This assists in analyzing the enterprise data, making IoT technology a core instrument in ensuring safe automated production, workforce monitoring, and personnel location tracking.
3. Asset Tracking
IoT technology combined with the development of native web and mobile apps for iOS or Android makes it possible to obtain real-time asset information and make reasonable decisions.
In tracking, the primary task is to discover and oversee the crucial assets such as the components of the supply chain — raw materials, containers, and finished goods. IoT integrated asset tracking apps can drastically help to optimize logistics, maintain stocks of work in progress, and disclose thefts and violations.
IoT-based asset tracking also helps the producers to calculate the usage of movable equipment elements and initiate measures to shorten the idle period and enhance utilization.
4. Logistics Management
Enterprises that depend greatly on transportation can also benefit from IoT-led interconnection between various devices and systems.
IoT can be employed to reveal supply chain inefficiencies by eliminating blind spots from logistics processes. Managing the automotive fleet via IoT-driven devices (autonomous fleet solutions) helps manufacturers eliminate or put down the risks concerning the costs related to vehicles, staff and transportation — contributing to the greater efficiency of the company.
Logistics managers can make good use of IoT when it comes to repairs and fuel expenditures by optimally monitoring fuel costs, smart deliveries, diagnostics, and drivers.
Additionally, a real-time overlook of driver and vehicle performance aids in raising technicians’ safety, bringing down inventory damage and reducing insurance payments.
5. Digital Twins
Digital Twins is an IoT approach that lets businesses create and enjoy robust digital copies of the physical objects manufactured by a company.
When empowered with IoT, a POC (proof of concept), an MVP (minimum viable product) or a look-and-feel prototype can be turned into an accurate digital copy. This can then be used to easily experiment on and foresee their functionality as well as initial and final operational capabilities.
This kind of IoT application can create a simulation of machines’ lifespans — which can be helpful in checking updates and predicting potential issues and bottlenecks.
With IoT instruments, producers can get a replica of equipment or goods that can be monitored in a virtual environment before releasing them in the market.
Finally, it helps to improve product quality, create efficient supply and delivery chains, open new opportunities for businesses, and propel customer service to new heights.
Implementing IoT solutions into your manufacturing plant or your commercial business process need not be a monumental hassle. With experts backed by credible hands-on field-experience, our team is highly equipped to provide custom, robust, end-to-end IoT solutions designed to empower and give your business an edge over your competition.
It’s no secret that our emotions drive our behaviours. But what if brands could leverage those emotions to deliver powerful messages that truly resonate with consumers? Believe it or not, this is already a reality thanks to Artificial Emotional Intelligence (Emotion AI). This technology combines behavioural and sensory data enabling brands to hyper-personalise physical and digital experiences both, online and offline, thus increasing sales. So how will this technology fundamentally change the way we cater to consumers?
Artificial Emotional Intelligence
Emotion AI is a form of emotion detection technology. It enables everyday objects to recognise our verbal and non-verbal behaviour and respond accordingly. Numerous tech giants and startups have been investing in Emotion AI for over a decade using various means such as algorithms, facial recognition and voice analysis to recognise human emotions. This disrupting technology will likely affect all industries from video games to marketing. It has the power to create more personalised user experiences and could help brands achieve real-time empathetic marketing, a concept that was once thought to be impossible. At a time when consumers are demanding a more human approach to marketing, this tech could help accomplish just that.
The Potential Of Emotion AI
Humans still have the upper hand when it comes to reading emotions but machines are gaining more ground using their own strengths: analysing large amounts of data in the blink of an eye. All of this data allows brands to develop a deeper, more nuanced understanding of their customers through recognising and interpreting human emotions.
This technology can also be used to further engage customers and build lasting relationships with them. For instance, marketers could implement chatbots which use AI technology to identify a customer’s personality traits and what drives their emotional responses regarding a company’s product selection or services. Based on an individual’s answers, the chatbot could direct them towards the most appropriate website content or, alternatively, a live customer service agent.
Such a simple tactic can be used by all industries to deliver a more relevant message to consumers. This is particularly important for B2B companies as on average, according to Google research, B2B customers are more emotionally connected to their vendors and service providers than consumers. Because a B2B customer isn’t only buying for himself, but for their entire company, thus a strong emotional affection and connection with their supplier is important.
But it doesn’t stop there, this technology can also be deployed in real-time to analyse consumer behaviour in-store. For example, the retail industry could use Emotion AI to understand how shoppers really feel about what they are buying — or not buying. Small sensors and cameras around product displays could show how people feel about prices, packaging and even branding. If people look at a price tag and frown, it might be good to lower prices. Alternatively, if shoppers analyse a product’s packaging and appear confused, you might want to redesign or simplify that packaging.
Lastly, if emotional responses suggest frustration when it comes to shelf placement and aisle arrangement, a small layout reconfiguration might be in order. So, this technology could also cater to consumer’s needs offline.
The Change Will Be Slow
With the promise to measure and engage consumers based on something once thought to be intangible, real-time empathetic marketing holds great potential for brands. But the adoption of this technology will be gradual given the amount of data it captures and its potentially intrusive nature. Consumers are more and more concerned about their privacy on the internet and many feel very uncomfortable at the thought of a video capturing and analysing their movements and facial expressions. As a result, this will slow down the application of Artificial Emotional Intelligence in marketing.
However, if your company decides to use Emotion AI, a key aspect to winning over consumer trust is to be transparent about what you are doing, how you are doing it, and what exactly you will use this data for. Transparency is crucial given how invasive this technology could be. Additionally, you could offer your customers a value exchange as a way of thanking them for their contribution.
Taking Personalisation To The Next Level
In the near future, businesses will have to shift their focus when trying to understand their customers and move past traditional sales metrics, focusing more on direct and indirect customer feedback. Then, as AI capabilities continue to improve, companies can leverage demographical, behavioural, and emotional data to more accurately reach their desired target audience and give them both a marketing message but also a product that they truly want.
So though this technology is still in the early stages of development, it will allow brands to deliver more relevant messages to highly segmented audiences and give them more meaningful experiences.
IoT (Internet of Things) technology is penetrating deeply into everyday human life. Cars, kitchen appliances, and even heart rate monitors connected via the Internet into one network where they exchange data. For example, having received data from the alarm clock in your smartphone, an IoT coffee maker will know when you get up for work and brew coffee at your desired time, down to the minute.
However, one of the most promising areas for the implementation of IoT devices is in healthcare. According to a study, six out of ten global healthcare organizations are already using IoT devices.
There are several positive trends observed due to this:
Medical staff are becoming more mobile.
The process of collecting, transferring, and analyzing patient data, as well as making a diagnosis, is accelerated.
The effectiveness of medical care is increasing.
IoT Devices for Patients
Patient monitoring sensors are the area where IoT comes the most in handy. Being placed in operating theatres, intensive care units, and post-surgery rooms, these devices will monitor the vitals of patients, and in case of dangerous situations, immediately notify doctors.
Such devices will help not only doctors and patients but also their relatives. For example, if a patient is going to have a difficult operation, an online location sensor can be attached to the patient’s body, to which their family can immediately know when the surgery is finished and receive its results.
A special sensor-based inpatient monitoring platform is being used which reads the patient’s vital signs round the clock and allows the medical staff to instantly respond to deterioration. In the future, there are plans to equip patients with such devices in cardiology and intensive care departments.
Another good example is a wearable device, which can predict a forthcoming epileptic seizure.
In many regions, there is still no easily accessible medical care. The transition to telemedicine has become an effective solution for this situation. A patient far away from any clinic or hospital is able to consult with a doctor in real-time and receive the necessary assistance before going to a medical facility.
Medical Equipment With IoT Technology
Monitoring sensors for hospital equipment can significantly improve the quality of medical services. Due to limited budgets, medical facilities can’t afford frequent replacements of necessary equipment. As a result, outdated equipment is in constant need of repairs.
IoT sensors can assess the state of the equipment and inform engineers about defects. This will allow for a quicker response time to breakdowns.
IoT devices can also help in monitoring the condition of the hospital premises. For instance, the sensor will take temperature readings in laboratories, freezers, and wards. If the temperature deviates from the norm, it will be possible to return it to the desired level remotely via Wi-Fi.
When transporting medicines that require a certain temperature, refrigerators with similar sensors can be useful. They will maintain the necessary temperature independently.
The Role of IoT in Medical Facility Management
IoT can also be deployed in solving the administrative and management challenges of the hospital. For instance, with the help of IoT devices, it is possible to keep track of the number of pharmaceuticals, the condition of the equipment, as well as identify the need to purchase replacements.
The Netherlands is already adopting a similar strategy. One hospital has a network that allows its staff to view available equipment and get quick access to patient data. This helps to avoid confusion and reduces the waiting time for medical procedures.
Navigation in huge hospital complexes is a challenge for patients and their families. A special application can help them find the required doctor’s office or ward by creating a route inside the building.
The future of IoT is extremely promising. The recent events have only highlighted the potential of harnessing IoT, Artificial Intelligence and Machine Learning for their improved efficiency and the factor of safety they offer in the field of healthcare — even in times of unimaginable crisis as that of COVID-19.
At NeoSOFT, we empower businesses and healthcare by helping them leverage the right IoT technology that suits their requirement and needs. Our experts work end-to-end on solutions that go beyond the realm of problem-solving and strive to provide meaningful value-addition. Contact us to discuss your ideas and we will realise them with an uncompromising promise of efficiency and safety.
The data explosion has put a massive strain on the data warehouse architecture. Organizations handle large volumes and different types of data, including sensor, social media, customer behaviour, and big data.
If your organization has a data warehouse, you’re most likely using either the extract, transform, load (ETL) or the extract, load, transform (ELT) data integration method.
ETL and ELT are two of the most popular methods of collecting data from multiple sources and storing it in a data warehouse which can be accessed by all the users in an organization.
ETL is the traditional method of data warehousing and analytics, but with technology advancements, ELT has now come into the picture. But what exactly happens when “T” and “L” switch places? Let’s discuss.
What is the difference between ETL and ELT?
In ETL, data is extracted from varying sources such as ERP and CRM systems, transformed (calculations are applied, raw data is changed into the required format/type, etc.), and then uploaded to the data warehouse, also called the target database.
In ELT, after extraction, data is first loaded in the target database and then transformed i.e., data transformation happens within the target database.
That said, the difference between these two processes isn’t just confined to the order in which data is integrated. To understand their differences, you also have to consider:
The underlying storage technologies
The design approach to data warehouse architecture
The business use cases for the data warehouse
What Changed and Why ELT Is Way Better?
1. Cloud-Based Computation and Storage of Data
The ETL approach was once necessary because of the high costs of on-premise computation and storage. With the rapid growth of cloud-based data warehouses and the plummeting cost of cloud-based computation and storage, there is little reason to continue transformation before loading at the final destination. Flipping the two enables analysts to do a better job in an autonomous way.
2. ELT Supports Agile Decision-Making for Analysts
When analysts can load data before transforming it, they don’t have to determine the required insights to be generated before deciding on the exact schema. Instead, the underlying source data is directly replicated to a data warehouse, comprising a “single source of truth.” Analysts can then perform transformations on the data as needed, with the flexibility of going back to the original data without compromising on its integrity. This makes the business intelligence process incomparably flexible and safer.
3. ELT Promotes Data Literacy Across the Whole Company
When used in combination with cloud-based business intelligence tools, the ELT approach also broadens access to a common set of analytics across organizations. Business intelligence dashboards become accessible even to relatively non-technical users.
The Bottom Line: Here are Some Final Thoughts About ETL and ELT
ETL is outdated. It works with traditional data center infrastructures, which cloud technologies are already replacing. The loading time takes hours, even for businesses with data sets that are just a few terabytes in size. ELT is the future of data warehousing and efficiently utilizes current cloud technologies. It allows businesses to analyze large data sets with lesser maintenance and offers key insights to help make the right business decisions. With time, the scope of ELT will potentially expand as native data integration tools continue to evolve.
Almost every college and university has moved towards e-learning platforms due to the pandemic. The introduction of learning management systems have made it easier for schools, colleges, and universities to reach out to students.
Stats show that the retention rate for students taking classes online is more compared to traditional classroom learning. The learning management system has proved to be an added advantage. With schools and universities cautious about opening up, it seems like e-learning platforms are only going to be getting more popular.
With the implementation of AI, the education world is about to scale to new heights and transform the learning sector like never before. The education system has already seen some of the impacts that artificial intelligence and machine learning have brought about. The aim is to create a new era where every student can understand their full potential and serve the society in the best way possible. Here are the recent advancements in AI that are reshaping the industry.
1. Content Creation
AI has the potential of creating content that is free from errors and of top-notch quality. It can take the burden of creating accurate and unique source material off the institutions, as well as circulating it securely.
Books need not be in the conventional format. With the implementation of voice recognition, audio-books can be created. It is proven that audio-books are more effective than traditional books. For students suffering from dyslexia or who lack reading prowess, these methods prove to be of great help.
2. Smart Mentoring Systems
It is hard to expect a teacher to give equal attention to every student in a classroom. That is where smart mentoring systems have a significant role to play. Based on the capacity of the student and their ability to grasp things, classes can be handled accordingly. Each student has different learning needs. A mentoring system would work on the student’s abilities and design a course according to their individual capabilities.
Plenty of online educational training institutions have opted for such a mode of teaching. Smart mentoring systems will not only help the students but also assist the teachers in equipping themselves according to the capability of the classroom.
3. Augmented Reality
There is a theory that if you create an experience, it stays with you for a lifetime. Augmented reality is based on a similar concept. Implementing this into the education system can genuinely transform the experience of learning. Students get to experience knowledge in the real world rather than just theoretically learning about it.
From ancient history to complex biology, work continues to convert all the academic knowledge into augmented reality. A future awaits us where students get to relive the World War. The hologram is another such method that uses the same principle.
Augmented reality will not only improve the educational standards but will create a future where students will be better equipped to come up with sophisticated solutions to indefinite problems. A global renaissance can be expected with the implementation of this technology.
4. Personalized Learning
Is it reasonable to expect a student to be good at everything? There are still schools where students are asked to be good at subjects they are not interested in. To eradicate this, a new methodology called personalized learning will likely be introduced. Based on the student’s preferences, a virtual mentor would be assigned to handle classes. Just like while binge-watching Netflix, a recommender engine algorithm will be introduced that will help the student choose their preferred subject. Fuelled by this concept, the world can see a rise in specialised Digital Universities where anyone can learn whatever they want.
5. AI-Based Virtual Assistants
Alexa and Siri have vastly impacted our day-to-day lives. Imagine harnessing something like that solely for education. AI-based virtual assistants, equipped with information, can bring everything at the tip of your fingers. They kickstart a whole new era of modern education, where instead of a teacher, a bot would be training the students. The speed, efficiency, and capacity to handle a vast number of students will increase greatly.
The future of education is not to be mistaken with a competition between bots and human teachers. The quest behind all these advancements is to empower human teachers and reimagine the educating experience by assisting them with AI. The objective is to not replace but to enhance the experience of gaining and imparting knowledge in an efficient manner and updated with times.