5 Marketing Technology Trends for 2020

| September 13, 2019
5 MARKETING TECHNOLOGY TRENDS FOR 2020
The aim of marketing is to make selling superfluous.” Peter F. Drucker   Tweet This! While selling is an art, it solely depends on the fact how much marketing efforts you have put in to make it possible. And when it comes to marketing efforts it will be incomplete unless you leverage modern technology to attain these marketing goals as ‘modern marketing requires modern solutions.’ These technologies when utilized effectively work wonders in terms of brand awareness and sales conversion. “Marketing is about values. It’s a complicated and noisy world, and we’re not going to get a chance to get people to remember much about us. No company is. So, we have to be really clear about what we want them to know about us.” -  Steve Jobs

Spotlight

Midea Carrier

Midea Carrier is the result of the union of Midea, the world leader in the production of household appliances, and Carrier, an international reference when it comes to air conditioning. The joint venture operates in Brazil, Argentina and Chile, and is now the largest manufacturer of air conditioning equipment in Latin America.

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Three Business Examples That Effectively Practice Lean Manufacturing

Article | December 13, 2021

Lean manufacturing principles enable manufacturing businesses to achieve spectacular results and overhaul their conventional operations. A wide range of industries have adopted lean manufacturing because of its enormous advantages, and they have seen excellent results as a result. The 2010 Compensation Data Manufacturing survey indicated that 69.7% of manufacturing organizations employ lean manufacturing principles. By consuming this data, we can understand how far organizations have progressed toward incorporating lean principles into their operations. “Many companies are not willing to change or think they are done once they make a change. But the truth is technology, consumer demands; the way we work, human needs, and much more are constantly changing.” –Michael Walton, Director, Manufacturing Industry Executive at Microsoft Let's look at some examples of lean manufacturing from some well-known companies. These leading-edge examples of lean manufacturing will shed light on how lean principles positively affect. Leading Companies Using Lean Manufacturing Effectively Successful manufacturing businesses like Toyota, Nike, and Caterpillar are currently employing lean manufacturing ideas in their production processes. In addition, Intel, Parker Hannifin, and John Deere embrace these techniques. From them, we've described three different organizations in various sectors that are successfully adopting lean manufacturing. JOHN DEERE John Deere has also implemented a lean manufacturing strategy. As a result, many of their quality control procedures are automated, which means that more components can be checked for flaws in less time. This means that more supply can be released each day, and the product can be supplied at a lower price to the consumer. Additionally, these controls monitor the manufacturing process for each component of their products, ensuring that they never manufacture more than is required and waste essential materials in the process. INTEL Intel, known for its computer processors, has used lean manufacturing techniques to provide a higher quality product for an industry that requires zero defects. In the past, it took more than three months to get a microprocessor to the manufacturer, but this principle has helped shorten that time to less than ten days. Intel rapidly learned that creating more but worse quality was not the way to raise revenues and increase consumer satisfaction with its products, which were extremely precise and technical. Instead, both parties gain from quality control and waste reduction initiatives. This is even true in the tech industry, where goods are constantly changed and upgraded. TOYOTA Toyota, the world's largest automaker, was the first to implement lean manufacturing in its manufacturing operations. But, even more importantly, they've learned how to limit products that don't match customer expectations by eliminating waste. To achieve these goals, Toyota employs two essential procedures. The first is a method known as Jidoka, which loosely translates as "automation with the assistance of humans." This implies that, although some of the work is automated, humans always ensure that the result is of the highest quality. When something goes wrong, the machines have built-in programs that allow them to shut themselves down. Known as the Just In Time (JIT) model, this is the second stage. Once the last part of a process has been finished, the next phase can begin. No unnecessary work will be done if there is a problem with the assembly line. This lean manufacturing technique has inspired thousands of other businesses. Final Words Lean manufacturing principles and their execution require discipline and patience to get the results out of them. When we see the successful lean manufacturing examples, it is not a fraction of a second success. They have devoted their time, energy, and efforts to modifying every single operational process in order to become a part of lean manufacturing. Lean manufacturing is not a method; it is a way of life that transforms your business practices and takes your firm to a new level of operations. Gain insights from renowned organizations' lean manufacturing success stories to help you become a part of the lean companies of 2022. FAQ What is the effect of lean manufacturing? Lean is a performance-based, continuous-improvement strategy that removes waste and unnecessary processes from organizational operations. As a result, your company becomes more focused on the results. Is it possible for lean manufacturing to fail? It is conceivable in some circumstances, such as failing to focus on a single system implementation or implementing too many system changes at once and failing to have a sound follow-up system to check that everything is working effectively. Why do certain businesses struggle with lean manufacturing? Most businesses fail to see that lean is a management philosophy, not a set of tools. As a result, most corporate leaders either don't understand or lack the patience and control to implement lean manufacturing. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What is the effect of lean manufacturing?", "acceptedAnswer": { "@type": "Answer", "text": "Lean is a performance-based, continuous-improvement strategy that removes waste and unnecessary processes from organizational operations. 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Building a Smart Factory is Possible Using Machine Learning

Article | December 7, 2021

Machine learning in manufacturing is becoming more widespread, with businesses like GE, Siemens, Intel, Bosch, NVIDIA, and Microsoft all investing heavily in machine learning-based ways to enhance manufacturing. Machine learning is predicted to expand from $1 billion in 2016 to USD 9 billion by 2022at a compound annual growth rate (CAGR) of 44% throughout the forecast period, according to Markets & Markets. The technology is being utilized to cut labor costs, achieve better transition times, and increase manufacturing speed. “I advocate business leaders get to know more about what AI can do and then leverage AI in proofs of concept.” – Michael Walton, Director and Industry Executive, Microsoft speaking with Media 7 Machine learning can help enhance manufacturing processes at the industrial level. This can be achieved by assessing current manufacturing models and identifying flaws and pain factors. Businesses can rapidly address any difficulties to keep the manufacturing pipeline running smoothly. Let us explore how machine learning is transforming manufacturing operations. How Machine Learning Is Transforming Manufacturing Operations “The greatest benefit of machine learning may ultimately be not what the machines learn but what we learn by teaching them.” - Pedro Domingos Machine learning in manufacturing is revolutionizing manufacturing operations and making them more advanced and result-oriented, so let's have a look at how this is unfolding. Allows for Predictive Maintenance Machine learning provides predictive maintenance by forecasting equipment breakdowns and eliminating wasteful downtime. Manufacturers spend far too much time correcting problems instead of planning upkeep. In addition to enhancing asset dependability and product quality, machine learning systems can forecast equipment breakdown with 92% accuracy. Machine learning and predictive analytics increased overall equipment efficiency from 65% to 85%. Increases Product Inspection and Quality Control Machine learning is also utilized for product inspection. Automated inspection and supervision using ML-based computer vision algorithms can discriminate between excellent and bad products. These algorithms simply need excellent samples to train; therefore a fault library is not required. However, an algorithm that compares samples to the most common errors can be built. Machine learning reduces visual quality control costs in manufacturing. Forbe's says AI-powered quality testing can boost detection rates by up to 80%. Logistics-related Tasks Are Automated To run a production line, industrial companies need considerable logistics skills. The use of machine learning-based solutions can improve logistics efficiency and save expenses. Manual, time-consuming operations like logistics and production-related documentation cost the average US business $171,340 annually. It saves thousands of manual working hours every year to automate these everyday procedures. Using Deep Mind AI, Google was able to lower its data center cooling bill by 40%. Creates More Business Opportunities Machine learning is frequently used in the production process. Substantial data analysis is required to create new items or improve existing products. Collection and analysis of huge amounts of product data can help find hidden defects and new business opportunities. This can help improve existing product designs and provide new revenue streams for the company. With machine learning, companies can reduce product development risks by making smarter decisions with better insights. Protects Company’s Digital Assets On-premise and cloud-based machine learning systems require networks, data, and technological platforms to function. Machine learning can help secure these systems and data by restricting access to vital digital platforms and information. Humans’ access sensitive data, choose applications, and connect to it using machine learning. This can help secure digital assets by immediately recognizing irregularities and taking appropriate action. Harley Davidson's Sales Climbed by 40% Using Albert – The ML & AI-Powered Robot Today, traditional marketing is harder to break through. It's easy to see why Albert (an AI-powered robot) would be a good fit for Harley Davidson NYC. Thanks to machine learning and artificial intelligence, robots are producing news stories, working in hotels, controlling traffic, and even running McDonald's. Albert works well with social media and email marketing. It analyzed which customers are more likely to convert and modifies the personal creative copies on its own for the next process. Harley-Davidson is the only company to employ Albert in its business. The company evaluated customer data to find prior consumers who made purchases and spent more time browsing the website than normal. Albert used this data to categorize customers and scale up test campaigns. Using Albert, Harley-Davidson's sales climbed by 40% and leads increased 2,930%, with half coming from high-converting ‘lookalikes' detected by AI and machine learning. Final Words The groundbreaking benefits of machine learning are the pillars of machine learning applications in manufacturing. Machine learning in manufacturing helps enhance productivity without compromising quality. According to Forbes, Amazon has automated warehouse logistics picking and packing using a machine learning system. With Kiva's help, Amazon's typical ‘click to ship' time dropped from 60-75 minutes to 15 minutes. So, industry leaders are seeing fantastic outcomes, and machine learning in manufacturing is the future. FAQ How is machine learning used in manufacturing? Machine learning is used in manufacturing to improve product quality and uncover new efficiencies. It unquestionably aids in the identification and removal of bottlenecks in the manufacturing process. Which two forms of machine learning are there? Machine learning is divided into two forms: supervised and unsupervised. In supervised machine learning, a machine learning algorithm is trained using data that has been labeled. Unsupervised ML has the advantage of working with unlabeled data. What is a machine learning model? A machine learning model is a file that can recognize patterns. In order to learn from a set of data, you must first train a model using an algorithm. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How is machine learning used in manufacturing?", "acceptedAnswer": { "@type": "Answer", "text": "Machine learning is used in manufacturing to improve product quality and uncover new efficiencies. 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Lead Generation for Manufacturers: 5 Effective Techniques That Work

Article | January 4, 2022

Lead generation for manufacturers has always been tough due to a lack of knowledge about new technology and trends that can help them generate more business leads. There are still a lot of small and mid-sized manufacturing companies that rely on antiquated manufacturer lead generation methods. In this article, we'll discuss some proven methods for generating leads that can help you increase your company's sales and improve your overall return on investment. "Don’t think of your lead as "LEADS." Instead, think of them as people who are frustrated because understanding and buying your product is too hard. Your job is to make it easy for them to learn about your product and get started. " —Andy Pitre, VP of Product, HubSpot So let's get started. Factors That Must Be Aligned to Drive New Business Leads Landing Pages Landing pages are mini-websites embedded into your site. To deliver an experience that speaks directly to the user's intent, marketers use landing pages. Create unique landing pages for every industrial lead generation campaign. Calls-To-Action To generate quality leads, you need to have a strong call to action (CTA). CTAs are usually buttons that allow users to submit information, visit a landing page, or download an e-book or white paper. Your CTA must be compelling. Give your prospects a reason to click and remove any barriers to the click. CTAs should be bold, high-contrast, and easily identifiable. Forms Without forms, it is impossible to collect leads. Therefore, visitors will be asked to fill out forms that collect their contact information in exchange for an offer. Offers Every lead contains a transaction. A company provides a valuable service in exchange for a prospect's contact information. You won't get many leads unless you provide value to your potential customers. This offer comes in the form of an e-book, consultation, coupon code, or whitepaper. To generate more leads, make compelling offers. Website The above components can't exist if you don't have a website. If you want to emphasize your business, you need to generate quality leads. Why? Because most of today's B2B buyers are millennials, who are highly tech-savvy and increasingly conduct their supplier research online. How to Generate Manufacturing Leads: 5 Effective Techniques Create a Website That Converts "The lead generation process starts by finding out where our target market ‘lives’ on the web." – Wayne Davis Your website should be a trusted source of quality leads. Unfortunately, many companies lose sight of this and develop websites that are cumbersome and difficult to browse, causing a rift between you and your potential customers. Don't expect people to behave if your site doesn't encourage them to act. Your website should have clear "call to action" buttons and lead capture options that allow visitors to contact you in a simple and pleasant way. Additionally, there are website optimization tools available, including PageSpeed Insights, Hotjar, Google Optimize, and WAVE. All of the above-mentioned website optimization tools provide complimentary services. So, this is the most accessible and most reliable approach to generating web leads. Make Descriptive Infographics Infographics are a great way to provide prospects with helpful information while motivating them to contact you. Most importantly, infographics establish your company as a thought leader and unconsciously identify you with industry authority. According to recent surveys, Nearly 41% of respondents indicated that infographics and illustrations are the most effective solutions for achieving their business objectives. On social media, infographics receive three times the number of shares as other types of content. Articles that included infographics received 72% more views than standard articles. A great infographic has a great design. If your organization lacks an in-house graphics team, you can simply locate a freelance designer to create a stunning infographic for you. Your infographics are ageless pieces of material that can be reused for smart marketing and lead generation manufacturing. Here's an example of an infographic from Digital Marketing Philippines from 2019 that received over 1,600 shares and is jam-packed with data and text. In this way, you can see how the company may have gotten its leads from these 1600 shares, each of which is a potential customer. Host an Event According to Bizzabo, 86% of senior management (Senior Managers, Executives, and Board Members) believe that in-person events are critical to the success of their company. The majority of B2B marketers (97%) believe in-person events have a significant impact on achieving business goals. According to Marketing Charts, 68% of B2B marketers agree that in-person events aid in lead generation for manufacturers, while case studies help with lead conversion and acceleration. Improve manufacturing lead generation through events that can occur both online and offline. Organize any kind of event to attract your target market while collecting contact information. Use live events to interact with consumers in real-time, answering questions, addressing objections, learning about your audience, and guiding prospects through the sales funnel. Consider webinars, workshops, seminars, meetups, and conferences. Create a Value-Packed Newsletter "Content is the fuel for your lead generation efforts." – Dayna Rothman According to the Content Marketing Institute, 31% of B2B marketers believe email newsletters are the most effective way to nurture leads. 81% of B2B marketers report that email newsletters are their most frequently used form of content marketing. Create a must-read newsletter that invites interested prospects to engage and remain connected with your company. This enables you to stay top-of-mind with consumers and promote your products and services to move prospects along the sales funnel. The newsletter can have new blog entries, product or service updates, special deals, upcoming events, and recommended reading from other thought leaders. Incorporate SEO into Your Marketing Plan According to Intergrowth, 61% of B2B marketers say SEO and organic traffic generate more leads than any other type of marketing. Search engine leads convert at a rate of 14.6%, while outbound leads (cold calling, direct mail, etc.) convert at a rate of 1.7%. Manufacturers are no exception when it comes to the importance of search engine optimization (SEO). As a result, you may generate many leads with the correct marketing approach and a profound grasp of SEO for manufacturers. Final Words When we consider the statistics explained earlier in this article, we can see the benefits of all of the techniques mentioned and how they can help you increase your lead generation and, as a result, your overall business ROI. Thus, we can refer to the above-mentioned lead generation techniques as sales-driven strategies that will assist you at every lead generation and conversion stage. Improved lead generation for manufacturers enables businesses to reach a vast customer base and generate more high-quality leads. FAQ What is a high-quality lead in manufacturing? Leads of high quality have an increased propensity to convert into paying consumers. The more qualified your leads are, the more likely they will buy your product or service. What are the lead generation challenges? Making accurate data, shaping conversations, and converting qualified leads into sales are some of the significant challenges in manufacturing lead generation.

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How Collaborative Robots Are Revolutionizing the Manufacturing Industry

Article | December 10, 2021

A new form of robot is entering manufacturing plants all around the globe. Instead of being locked away in their own work cell, collaborative robots work side by side with their human counterparts. Together, they form the manufacturing crew of the future. Collaborative robots, or cobots, are more flexible, easy to use, and safer than industrial robots. Instead of ending up abandoned in a corner, they are proving to be serious expansions of production capacity leading to better ways of creating superior quality products. 1.1 A New Breed of Bot Cobots are a new type of automation product with their own ISO standards for safety and usability. For a robot to qualify as a cobot, it has to be used for tasks of a collaborative nature while sharing all or part of its reach space with human operators. So it is not the product alone that classifies it as a cobot. Industrial robots must be expertly programmed for one specific job along the production line. This requires hard line coding and endless tweaking and testing, which together with other factors make for a sizable upfront investment. Not so with collaborative robots. Cobots may look similar to traditional robots in some ways, but they are much easier to install and program. This foregoes the need to cooperate with a robotic integration service. Their lightweight and friendly form factor lets manufacturers conveniently relocate them on the shopfloor from one project to another. This renders the robotics technology perfect for a data-driven, Industry 4.0 work environment. Cobots can side with traditional machinery and additive manufacturing equipment, aided by artificial intelligence and cloud connectivity while embedded in a networked environment rich with smart sensors and mixed reality interfaces. 1.2 A Unique Blend of Benefits Because it is fairly straightforward to reprogram a cobot to various tasks, they are perfect for high-mix, low-volume work to meet the rising demand for ultra-customized products. They can also do multiple tasks in unison, such as alternatingly loading a machine and finishing parts from the previous cycle. Here are some other advantages in addition to flexibility: • Low investment. Cobots typically cost a fraction of the price of an industrial robot, but they offer much lower payload and reach. ROI is typically one to two years. • Safety. With rounded surfaces, force-limited joints, and advanced vision systems, cobots are exceptionally safe. This reduces the risk of injury due to impact, crushing, and pinching. Driverless transport systems are wheeled mobile robots that immediately halt when their lasers detect the presence of a nearby human being. • Accuracy. Cobots score well on accuracy with 0.1mm precision or well below that. While they do typically sacrifice speed, dual-mode cobots can be converted to fully-fledged tools of mass production that run at full speed in their own safeguarded space. • Easy to program. Many brands offer user-friendly programming interfaces from beginner to expert level. This reduces the need for continuous availability of expensive and scarce expertise while giving current employees an incentive to upskill. And because they can be deployed within hours, cobots can be leased for temporary projects. • Research. Small processing plants, agile start-ups, and schools can invest in cobots to experiment with ways to automate processes before committing to full automation. 1.3 Cobot Activity Repertoire Cobots are perfect candidates for taking over strenuous, dirty, difficult, or dull jobs previously handled by human workers. This relieves their human co-workers from risk of repetitive strain injury, muscle fatigue, and back problems. They can also increase job satisfaction and ultimately a better retirement. The cobot’s program of responsibilities includes: • Production tasks such as lathing, wire EDM, and sheet stamping. • Welding, brazing, and soldering. • Precision mounting of components and fasteners, and applying adhesive in various stages of general assembly. • Part post-finishing such as hole drilling, deburring, edge trimming, deflashing, sanding, and polishing. • Loading and unloading traditional equipment such as CNC and injection molding machines, and operating it using a control panel to drastically reduce cycle times. • Post-inspection such as damage detection, electronic circuit board testing, and checking for circularity or planarity tolerances. • Box-packing, wrapping, and palletizing. • Automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) assist with internal transport and inventory management. 1.4 No-Code Programming While an industrial robot requires the attention of a high-paid robotics engineer, anyone with basic programming savviness can install and maintain a collaborative unit. Brands are releasing more and more kits for quick installation and specific use cases. Instead of being all numbers and line-coding, current user interaction is exceptionally people-focused. At the lowest skill level, lead-through programming lets operators physically guide the cobot’s end-of-arm-tool (EOAT) through the desired motion path, after which it will flawlessly replicate the instructed behaviour. It is also possible to enter desired waypoints as coordinates. At the highest level, it is of course still possible to have full scripting control. An intermediate step is visual programming interfaces. These let users create blocks of functionality that they can string together into more advanced action sequences, while entering the appropriate parameters for each function such as gripping strength, screwing tightness, or pressing force. These UIs come in the form of in-browser or mobile apps. Based on a 3D-CAD model of the machine and its industrial environment, a digital twin of the cobot can simulate and optimize its operations, for example to prevent collisions. It also lets operators remotely monitor and adjust the machine while it’s running. All the while, back-end artificial intelligence can do its analyses to find further efficiency improvements. 3D models of the to-be-manufactured product can be imported for edge extraction of complex surfaces. These will then be converted into the cobot’s desired movement trajectories instead of tedious manual programming. This makes them feasible to implement for highly dexterous tasks like welding curved hydroformed metal parts or sanding and polishing the most intricate of 3D printed geometries. Interfacing directly with the robot is becoming increasingly human-centered as well. Future cobots will respond to voice interaction as well as touch input, eradicating the screens-and-buttons paradigm of current devices. Some brands are giving the cobot a face with emotional expressions, hoping to lower the barrier to adoption. The upcoming generation of cobots can even respond to body language, as well as show its intentions by projecting light to where they are about to reach or move next. 1.5 A Human World Ultimately, the objective of any company is to create value for people. It is not an option to completely remove humans from the shop floor in an attempt to stay at the forefront of innovation. Attempting to leap to full automation and the utopian “lights-out factory” does not work anyway, as automotive giants such as Ford, Chrysler, GM, and Tesla can testify. A significant portion of human employees will indeed need to give up their roles. On the other hand, improved productivity levels open up space to retain personnel and uplift them to more creative, managerial, analytical, social, or overall more enjoyable jobs. For certain tasks, humans still need to be kept inside the manufacturing loop. For example: • Complex assembly routines and handling of flexible components. • Large vehicle subassemblies contain many variable components and require more hand-eye coordination than one cobot can handle. Humans are needed to make sure everything lands in the right position while the cobot provides assistive muscle power. • Fashion, footwear, jewellery, art pieces, and other products where creation borders on artistry rather than mechanical assembly require the aesthetic eye of humans. People are also needed to spot aesthetic deficiencies in custom one-offs in order to correspond with customers before finishing the production batch. • While intelligent automation software can spot bottlenecks in efficiency, humans are required for creative problem solving and context-awareness to make decisions. A spirit of flexibility and innovation is just as important as the accuracy of perfect repetitions. 1.6 Mission: Install a Cobot Cobots have numerous advantages over industrial solutions or people-only workspaces. They enable faster, more precise, and more sophisticated operations while reducing downtime and maintaining employee satisfaction. Low-voltage operation and reduced material waste fits with sustainable innovation and corporate social responsibility programs. Many companies are reporting surges in production capacity and staff generally experience the presence of cobots as favorable. For example, industry leviathans like BMW and Mercedes-Benz are reaching the conclusion that in many parts of the production process implementing a cobot has been the right decision. Connecting all parts of the production line with full automation solutions is a pipedream. It works only when all steps are perfectly attuned, and in reality this never happens and one misstep can be catastrophic. Whether to hire a human, a robot, or a co-robot is a complex and ever-more pressing decision. Statistical process control is paramount for large organizations to make unbiased data-driven decisions. Determine the key performance indicators, then find the most critical bottlenecks and major opportunities for leaps in production efficiency, product quality, or staff unburdening. Talk to employees for their insights and probe their level of skill and enthusiasm needed for working with their new artificial assistants. Digital transformation should be an exciting shift in the organization and its people, so apply new technological advancements only where it makes sense. Despite common beliefs about robotization, the cobot is an entirely separate product category that can be a surprisingly plug-and-play solution for simple tasks, with programming apps becoming increasingly intuitive. A cobot’s flexibility makes it perfect to run early experiments to help companies find its best spot on the factory floor. Its unbelievable precision, consistency, and level of control generally can make a strong first impression on customers. Not only can cobots increase production capacity while reducing idle time and cycle time to accelerate manufacturing across many vertical markets, but they also enrich the work environment resulting in happier and more involved employees. For many companies, a cobot can be the next logical step in their digital transformation.

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Spotlight

Midea Carrier

Midea Carrier is the result of the union of Midea, the world leader in the production of household appliances, and Carrier, an international reference when it comes to air conditioning. The joint venture operates in Brazil, Argentina and Chile, and is now the largest manufacturer of air conditioning equipment in Latin America.

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