Content Marketing Trends To Watch In 2017 [INFOGRAPHIC]

Michael Brenner

Content marketing is quickly becoming a game-changer in the field of marketing.

Since the rise of digital, social, and mobile, various businesses and brands have attempted to get closer and be more human with their customers. This fosters loyalty and trust, ensuring the growth of their business.

In addition, content marketing establishes your brand as an authority. Delivering content that is both timely and helpful for the niche it is aimed at builds your brand as one that genuinely knows its customers and the problems they face, and understands how to help them overcome these obstacles.

Being an authority builds trust – something that customers rely on when making purchasing decisions.

Great content is also beneficial for your SEO. Blogs with quality content and are greatly connected to your brand have positive effects.

Googles’ updates in recent years take into consideration the quality of content that websites put out, and they reward quality and punish ones with over-optimized or “spammy” content with too many keywords that add no real value to the content. The better Google rates your content, the stronger the chance you land on a higher position on search engine results pages (SERPs).

Lastly, quality content adds value to your audience. This is an important factor to keep customers coming back to your website and to your brand.

Quality content gives customers a worthwhile experience and makes them more likely to engage with you. Engagement ranks especially important to brands that are looking to increase their relations with customers and is a great indicator of customer loyalty and trust.

However, many still carry misconceptions about content marketing, believing that it’s enough to post in their social media feeds and let the rest flow from there.

The Content Marketing Institute defines content marketing as a “strategic marketing approach focused on creating and distributing valuable, relevant, and consistent content to attract and retain a clearly defined audience – and ultimately, to drive profitable customer action.”

This means that effective strategies must be implemented to maximize efforts for the business.

To start, you must fully understand the goals of your content marketing strategy and a clearly defined audience identity that goes beyond simple demographics.

You must be specific about what you want to accomplish as this will help you target and focus on execution instead of wasting effort and budget on other executions that may not work with your audience.

You should also know your audience on a deep level. Demographics are great, but they aren’t nearly enough. Identify their wants, needs, interests, questions, and concerns. From there, figure out how your product or service can fit into their lives and what expertise can be of use to them. This will enable you to create content that informs, entertains, and engages them effectively and meaningfully.

Content marketing strategy doesn’t involve only these factors. The success or failure of a content marketing strategy also depends on anticipating and adapting to changing trends in the content marketing sphere. These dictate the most likely methods or aspects that will be seen in the landscape of content marketing. Having a strong grasp of them early on lets you adapt to the changes beforehand, setting you up for success earlier than your competition.

With that in mind, here are the top content marketing trends to watch out for in 2017, as presented in an infographic by CJG Digital Marketing:

Content Marketing Trends

Embedded from CJG Digital Marketing

For more on content marketing strategies, see Not Good At Content Marketing? Try Simplifying Your Strategy.


About Michael Brenner

Michael Brenner is a globally-recognized keynote speaker, author of  The Content Formula and the CEO of Marketing Insider GroupHe has worked in leadership positions in sales and marketing for global brands like SAP and Nielsen, as well as for thriving startups. Today, Michael shares his passion on leadership and marketing strategies that deliver customer value and business impact. He is recognized by the Huffington Post as a Top Business Keynote Speaker and   a top  CMO influencer by Forbes.

This Is the Dawning Of The Age Of The … Webinerd?

Fred Isbell

On a recent flight home from San Francisco, I was reminded of the first time I traveled to this amazing city. The year was 1968, and it was near the end of an epic three-week family summer adventure. The brightest memory of that journey included a tour of San Francisco. It was just after the Summer of Love and during the height of popularity for the musical Hair. This was the year where “this is the dawning of the age of Aquarius” was forever etched into my consciousness as I walked in this awe-inspiring place among the “flower children.”

Fast forward 50 years. I’m no longer that small boy. In fact, even my own kids are now in their 20s – the same age as many of the people I saw during that magical visit to San Francisco a half-century ago. I’ve been back many times since that trip. But knowing I would face a homecoming of a foot-and-a-half of snow and no power or heat, I felt sad about heading back East after such a great event.

This year, I came to San Francisco to attend and speak at ON24 Webinar World 2018. I was very fortunate to be the SAP keynote at the inaugural Webinar World 2017 event, along with my good friend and SAP colleague Scott Feldman. Last year we had fun noting that 500 people had traveled to a physical event about virtual webinars – but this year, the audience grew to over 1,000 people. I hosted a breakout session on “The Art & Science of Modern Marketing: Three Key Best Practices for the Journey,” which focused on three modern marketing topics: thought leadership, the modern webinar, and performance management and analytics.



During the conference, ON24 gave out T-shirts with #webinerd prominently displayed. Many attendees proudly wore those shirts during the two-day event. Although you will hear more from me about this event, I’ll say that there was as much love and passion in the air (albeit for digital marketing and modern webinars) at ON24 Webinar World 2018 as there was in the Summer of Love. It’s truly a special time when people aligned around a common purpose all converge and share insights, best practices, and, yes, the love of what they do. This event was a celebration of modern marketing, the rise of digital marketing fueled by a demand-generation platform, data-driven marketing, and authentic real-time insights.

So if anyone asks: Yes! We are experiencing the dawning of the age the Webinerd. And with it, we are in the midst of a fascinating evolution of modern marketing fueled by digitalization and marketing technology (MarTech).

Check out the social media coverage of Webinar World 2018 I tweeted during this amazing couple of days.

Special thanks to ON24 and everyone who attended Webinar World 2018 for this fantastic experience and inspiring this blog.

Digital marketing has escaped the confines of the marketing department; In a Live Business, Social Gets Its MBA.


About Fred Isbell

Fred Isbell is the Senior Director of SAP Digital Business Services Marketing at SAP. He is an experienced, results- and goal-oriented senior marketing executive with broad and extensive experience & expertise in high technology and marketing. He has a BA from Yale and an MBA from the Duke Fuqua School of Business.

Take Back Your Customers With IoT Initiatives

Joerg Koesters

It’s clear: The retail industry is changing at a rapid pace. It has never been so important for retailers to grab hold of their customers and create new sales points, drive better engagement, and build brand loyalty. The implementation of IoT can provide that important connection point for retailers and customers, providing a new way for retailers to engage with and meet the needs of their customers.

Retail trends are worrisome: A jumpstart with IoT can change it all

By April of 2017, the U.S. had lost 30,000 positions in the retail industry, and CoStar Group reported that 10 percent, or 1 billion square feet of retail space, would shutter by the end of the year. In the UK, continued Brexit concerns plague the retail industry. In Australia, there’s a growing concern about Amazon moving into a retail market already struggling to stay alive. These key trends are worrisome for retailers.

The key here is that consumers are still buying. In some cases, consumer spending is up. The problem is, it’s much easier to buy what’s needed online and wait for it to arrive rather than head to a store. That’s what retailers need to change. They need to give consumers a better experience when they walk in the door to convince them to come more often, buy more, and increase their brand loyalty. IoT can help with that.

At the same time, most retailers today see the value of turning their attention to improving e-commerce operations. Implementing the right technology can ensure that shopping carts are not left empty and that consumers always have an idea of what is in stock and ready to buy.

Retailers secure profitability again through the connected customer

Retailers have an interest in IoT. It provides improvements in inventory management, asset management, and consumer experience-driven sales. The simplest explanation of the future of retail is that IoT will become a critical enabler of the shopping experience. What does the connected customer expect? What can they provide to the industry?

IoT improves customer satisfaction

A key component of IoT in the retail experience is its ability to enhance customer satisfaction. Happy customers translate into stronger loyalty, larger transactions, and more frequent visits to retail locations. IoT can connect people, including customers, associates, and service providers, directly to products and to product information.

That means it can help to improve the visibility of product. Consumers know what’s available, and that drives their ability and willingness to purchase now. It also reduces inaccuracies in inventory availability. This is one of the most common reasons e-commerce retailers see abandoned order carts, customer dissatisfaction, and even brand switching.

Profitability increases

With more customer satisfaction and loyalty, retailers see long-term profitability rise. Initially, this means bigger checks, but it also means increased sell-through. It improves profitability overall but also reduces the need to mark down products now, a critical concern for many retailers today. Consumers have become accustomed to buying only when there’s a sale or discount. Retailers no longer have to mark down their product to see sales as frequently.

Personalized marketing drives better sales performance

Finally, IoT creates personalized marketing opportunities for retailers. This type of marketing is perhaps the most important component of physical store marketing going forward. Personalized marketing is the ability to send specific messages of sales, opportunities, or product awareness to a consumer that’s most likely to buy. This leads to higher conversion rates and better sales performance in every scenario.

The changing retail sector is more consumer-focused than ever

It’s estimated that 70 percent of retail decision makers across the globe are adopting IoT to improve customer experiences. Another key fact from the Zebra 2017 Retail Vision Study says that 90 percent of retailers plan to implement some type of buy-online/pickup-in-store plan within the next four years. As these details demonstrate, there’s a growing need to change the way you do business to meet the needs of today’s consumer.

Imagine, for a moment, how personalized marketing could work for the average retail location. A consumer stops at a shopping mall. The mall’s implemented IoT system notices the consumer based on his or her opt-in app. It can provide insight into the latest discounts or perhaps offer in-store purchases in a flash sale. Retailer A sees that this consumer, who purchased a specific product from them, is nearby. The retailer can ping the consumer’s phone, offer a flash sale on that item or provide information about bulk inventory, and the customer benefits. This creates instant satisfaction to the consumer and provides a clear opportunity for the retailer, and the shopping center, to connect and engage their consumer.

The key here is the technology behind IoT. With the most effective system in place, including the hardware, software, and connectivity, it becomes possible to embrace a better customer-retail connection. Of course, having the framework in place and the tools to pull in and analyze that data is the critical first step. From there, the more companies implement IoT strategies, the more they will comprehensively change the retail atmosphere.

Learn how to innovate at scale by incorporating individual innovations back to the core business to drive tangible business value: Accelerating Digital Transformation in Retail. Explore how to bring Industry 4.0 insights into your business today: Industry 4.0: What’s Next?


About Joerg Koesters

Joerg Koesters is the Head of Retail Marketing and Communication at SAP. He is a Technology Marketing executive with 20 years of experience in Marketing, Sales and Consulting, Joerg has deep knowledge in retail and consumer products having worked both in the industry and in the technology sector.

The Blockchain Solution

By Gil Perez, Tom Raftery, Hans Thalbauer, Dan Wellers, and Fawn Fitter

In 2013, several UK supermarket chains discovered that products they were selling as beef were actually made at least partly—and in some cases, entirely—from horsemeat. The resulting uproar led to a series of product recalls, prompted stricter food testing, and spurred the European food industry to take a closer look at how unlabeled or mislabeled ingredients were finding their way into the food chain.

By 2020, a scandal like this will be eminently preventable.

The separation between bovine and equine will become immutable with Internet of Things (IoT) sensors, which will track the provenance and identity of every animal from stall to store, adding the data to a blockchain that anyone can check but no one can alter.

Food processing companies will be able to use that blockchain to confirm and label the contents of their products accordingly—down to the specific farms and animals represented in every individual package. That level of detail may be too much information for shoppers, but they will at least be able to trust that their meatballs come from the appropriate species.

The Spine of Digitalization

Keeping food safer and more traceable is just the beginning, however. Improvements in the supply chain, which have been incremental for decades despite billions of dollars of technology investments, are about to go exponential. Emerging technologies are converging to transform the supply chain from tactical to strategic, from an easily replicable commodity to a new source of competitive differentiation.

You may already be thinking about how to take advantage of blockchain technology, which makes data and transactions immutable, transparent, and verifiable (see “What Is Blockchain and How Does It Work?”). That will be a powerful tool to boost supply chain speed and efficiency—always a worthy goal, but hardly a disruptive one.

However, if you think of blockchain as the spine of digitalization and technologies such as AI, the IoT, 3D printing, autonomous vehicles, and drones as the limbs, you have a powerful supply chain body that can leapfrog ahead of its competition.

What Is Blockchain and How Does It Work?

Here’s why blockchain technology is critical to transforming the supply chain.

Blockchain is essentially a sequential, distributed ledger of transactions that is constantly updated on a global network of computers. The ownership and history of a transaction is embedded in the blockchain at the transaction’s earliest stages and verified at every subsequent stage.

A blockchain network uses vast amounts of computing power to encrypt the ledger as it’s being written. This makes it possible for every computer in the network to verify the transactions safely and transparently. The more organizations that participate in the ledger, the more complex and secure the encryption becomes, making it increasingly tamperproof.

Why does blockchain matter for the supply chain?

  • It enables the safe exchange of value without a central verifying partner, which makes transactions faster and less expensive.
  • It dramatically simplifies recordkeeping by establishing a single, authoritative view of the truth across all parties.
  • It builds a secure, immutable history and chain of custody as different parties handle the items being shipped, and it updates the relevant documentation.
  • By doing these things, blockchain allows companies to create smart contracts based on programmable business logic, which can execute themselves autonomously and thereby save time and money by reducing friction and intermediaries.

Hints of the Future

In the mid-1990s, when the World Wide Web was in its infancy, we had no idea that the internet would become so large and pervasive, nor that we’d find a way to carry it all in our pockets on small slabs of glass.

But we could tell that it had vast potential.

Today, with the combination of emerging technologies that promise to turbocharge digital transformation, we’re just beginning to see how we might turn the supply chain into a source of competitive advantage (see “What’s the Magic Combination?”).

What’s the Magic Combination?

Those who focus on blockchain in isolation will miss out on a much bigger supply chain opportunity.

Many experts believe emerging technologies will work with blockchain to digitalize the supply chain and create new business models:

  • Blockchain will provide the foundation of automated trust for all parties in the supply chain.
  • The IoT will link objects—from tiny devices to large machines—and generate data about status, locations, and transactions that will be recorded on the blockchain.
  • 3D printing will extend the supply chain to the customer’s doorstep with hyperlocal manufacturing of parts and products with IoT sensors built into the items and/or their packaging. Every manufactured object will be smart, connected, and able to communicate so that it can be tracked and traced as needed.
  • Big Data management tools will process all the information streaming in around the clock from IoT sensors.
  • AI and machine learning will analyze this enormous amount of data to reveal patterns and enable true predictability in every area of the supply chain.

Combining these technologies with powerful analytics tools to predict trends will make lack of visibility into the supply chain a thing of the past. Organizations will be able to examine a single machine across its entire lifecycle and identify areas where they can improve performance and increase return on investment. They’ll be able to follow and monitor every component of a product, from design through delivery and service. They’ll be able to trigger and track automated actions between and among partners and customers to provide customized transactions in real time based on real data.

After decades of talk about markets of one, companies will finally have the power to create them—at scale and profitably.

Amazon, for example, is becoming as much a logistics company as a retailer. Its ordering and delivery systems are so streamlined that its customers can launch and complete a same-day transaction with a push of a single IP-enabled button or a word to its ever-attentive AI device, Alexa. And this level of experimentation and innovation is bubbling up across industries.

Consider manufacturing, where the IoT is transforming automation inside already highly automated factories. Machine-to-machine communication is enabling robots to set up, provision, and unload equipment quickly and accurately with minimal human intervention. Meanwhile, sensors across the factory floor are already capable of gathering such information as how often each machine needs maintenance or how much raw material to order given current production trends.

Once they harvest enough data, businesses will be able to feed it through machine learning algorithms to identify trends that forecast future outcomes. At that point, the supply chain will start to become both automated and predictive. We’ll begin to see business models that include proactively scheduling maintenance, replacing parts just before they’re likely to break, and automatically ordering materials and initiating customer shipments.

Italian train operator Trenitalia, for example, has put IoT sensors on its locomotives and passenger cars and is using analytics and in-memory computing to gauge the health of its trains in real time, according to an article in Computer Weekly. “It is now possible to affordably collect huge amounts of data from hundreds of sensors in a single train, analyse that data in real time and detect problems before they actually happen,” Trenitalia’s CIO Danilo Gismondi told Computer Weekly.

Blockchain allows all the critical steps of the supply chain to go electronic and become irrefutably verifiable by all the critical parties within minutes: the seller and buyer, banks, logistics carriers, and import and export officials.

The project, which is scheduled to be completed in 2018, will change Trenitalia’s business model, allowing it to schedule more trips and make each one more profitable. The railway company will be able to better plan parts inventories and determine which lines are consistently performing poorly and need upgrades. The new system will save €100 million a year, according to ARC Advisory Group.

New business models continue to evolve as 3D printers become more sophisticated and affordable, making it possible to move the end of the supply chain closer to the customer. Companies can design parts and products in materials ranging from carbon fiber to chocolate and then print those items in their warehouse, at a conveniently located third-party vendor, or even on the client’s premises.

In addition to minimizing their shipping expenses and reducing fulfillment time, companies will be able to offer more personalized or customized items affordably in small quantities. For example, clothing retailer Ministry of Supply recently installed a 3D printer at its Boston store that enables it to make an article of clothing to a customer’s specifications in under 90 minutes, according to an article in Forbes.

This kind of highly distributed manufacturing has potential across many industries. It could even create a market for secure manufacturing for highly regulated sectors, allowing a manufacturer to transmit encrypted templates to printers in tightly protected locations, for example.

Meanwhile, organizations are investigating ways of using blockchain technology to authenticate, track and trace, automate, and otherwise manage transactions and interactions, both internally and within their vendor and customer networks. The ability to collect data, record it on the blockchain for immediate verification, and make that trustworthy data available for any application delivers indisputable value in any business context. The supply chain will be no exception.

Blockchain Is the Change Driver

The supply chain is configured as we know it today because it’s impossible to create a contract that accounts for every possible contingency. Consider cross-border financial transfers, which are so complex and must meet so many regulations that they require a tremendous number of intermediaries to plug the gaps: lawyers, accountants, customer service reps, warehouse operators, bankers, and more. By reducing that complexity, blockchain technology makes intermediaries less necessary—a transformation that is revolutionary even when measured only in cost savings.

“If you’re selling 100 items a minute, 24 hours a day, reducing the cost of the supply chain by just $1 per item saves you more than $52.5 million a year,” notes Dirk Lonser, SAP go-to-market leader at DXC Technology, an IT services company. “By replacing manual processes and multiple peer-to-peer connections through fax or e-mail with a single medium where everyone can exchange verified information instantaneously, blockchain will boost profit margins exponentially without raising prices or even increasing individual productivity.”

But the potential for blockchain extends far beyond cost cutting and streamlining, says Irfan Khan, CEO of supply chain management consulting and systems integration firm Bristlecone, a Mahindra Group company. It will give companies ways to differentiate.

“Blockchain will let enterprises more accurately trace faulty parts or products from end users back to factories for recalls,” Khan says. “It will streamline supplier onboarding, contracting, and management by creating an integrated platform that the company’s entire network can access in real time. It will give vendors secure, transparent visibility into inventory 24×7. And at a time when counterfeiting is a real concern in multiple industries, it will make it easy for both retailers and customers to check product authenticity.”

Blockchain allows all the critical steps of the supply chain to go electronic and become irrefutably verifiable by all the critical parties within minutes: the seller and buyer, banks, logistics carriers, and import and export officials. Although the key parts of the process remain the same as in today’s analog supply chain, performing them electronically with blockchain technology shortens each stage from hours or days to seconds while eliminating reams of wasteful paperwork. With goods moving that quickly, companies have ample room for designing new business models around manufacturing, service, and delivery.

Challenges on the Path to Adoption

For all this to work, however, the data on the blockchain must be correct from the beginning. The pills, produce, or parts on the delivery truck need to be the same as the items listed on the manifest at the loading dock. Every use case assumes that the data is accurate—and that will only happen when everything that’s manufactured is smart, connected, and able to self-verify automatically with the help of machine learning tuned to detect errors and potential fraud.

Companies are already seeing the possibilities of applying this bundle of emerging technologies to the supply chain. IDC projects that by 2021, at least 25% of Forbes Global 2000 (G2000) companies will use blockchain services as a foundation for digital trust at scale; 30% of top global manufacturers and retailers will do so by 2020. IDC also predicts that by 2020, up to 10% of pilot and production blockchain-distributed ledgers will incorporate data from IoT sensors.

Despite IDC’s optimism, though, the biggest barrier to adoption is the early stage level of enterprise use cases, particularly around blockchain. Currently, the sole significant enterprise blockchain production system is the virtual currency Bitcoin, which has unfortunately been tainted by its associations with speculation, dubious financial transactions, and the so-called dark web.

The technology is still in a sufficiently early stage that there’s significant uncertainty about its ability to handle the massive amounts of data a global enterprise supply chain generates daily. Never mind that it’s completely unregulated, with no global standard. There’s also a critical global shortage of experts who can explain emerging technologies like blockchain, the IoT, and machine learning to nontechnology industries and educate organizations in how the technologies can improve their supply chain processes. Finally, there is concern about how blockchain’s complex algorithms gobble computing power—and electricity (see “Blockchain Blackouts”).

Blockchain Blackouts

Blockchain is a power glutton. Can technology mediate the issue?

A major concern today is the enormous carbon footprint of the networks creating and solving the algorithmic problems that keep blockchains secure. Although virtual currency enthusiasts claim the problem is overstated, Michael Reed, head of blockchain technology for Intel, has been widely quoted as saying that the energy demands of blockchains are a significant drain on the world’s electricity resources.

Indeed, Wired magazine has estimated that by July 2019, the Bitcoin network alone will require more energy than the entire United States currently uses and that by February 2020 it will use as much electricity as the entire world does today.

Still, computing power is becoming more energy efficient by the day and sticking with paperwork will become too slow, so experts—Intel’s Reed among them—consider this a solvable problem.

“We don’t know yet what the market will adopt. In a decade, it might be status quo or best practice, or it could be the next Betamax, a great technology for which there was no demand,” Lonser says. “Even highly regulated industries that need greater transparency in the entire supply chain are moving fairly slowly.”

Blockchain will require acceptance by a critical mass of companies, governments, and other organizations before it displaces paper documentation. It’s a chicken-and-egg issue: multiple companies need to adopt these technologies at the same time so they can build a blockchain to exchange information, yet getting multiple companies to do anything simultaneously is a challenge. Some early initiatives are already underway, though:

  • A London-based startup called Everledger is using blockchain and IoT technology to track the provenance, ownership, and lifecycles of valuable assets. The company began by tracking diamonds from mine to jewelry using roughly 200 different characteristics, with a goal of stopping both the demand for and the supply of “conflict diamonds”—diamonds mined in war zones and sold to finance insurgencies. It has since expanded to cover wine, artwork, and other high-value items to prevent fraud and verify authenticity.
  • In September 2017, SAP announced the creation of its SAP Leonardo Blockchain Co-Innovation program, a group of 27 enterprise customers interested in co-innovating around blockchain and creating business buy-in. The diverse group of participants includes management and technology services companies Capgemini and Deloitte, cosmetics company Natura Cosméticos S.A., and Moog Inc., a manufacturer of precision motion control systems.
  • Two of Europe’s largest shipping ports—Rotterdam and Antwerp—are working on blockchain projects to streamline interaction with port customers. The Antwerp terminal authority says eliminating paperwork could cut the costs of container transport by as much as 50%.
  • The Chinese online shopping behemoth Alibaba is experimenting with blockchain to verify the authenticity of food products and catch counterfeits before they endanger people’s health and lives.
  • Technology and transportation executives have teamed up to create the Blockchain in Transport Alliance (BiTA), a forum for developing blockchain standards and education for the freight industry.

It’s likely that the first blockchain-based enterprise supply chain use case will emerge in the next year among companies that see it as an opportunity to bolster their legal compliance and improve business processes. Once that happens, expect others to follow.

Customers Will Expect Change

It’s only a matter of time before the supply chain becomes a competitive driver. The question for today’s enterprises is how to prepare for the shift. Customers are going to expect constant, granular visibility into their transactions and faster, more customized service every step of the way. Organizations will need to be ready to meet those expectations.

If organizations have manual business processes that could never be automated before, now is the time to see if it’s possible. Organizations that have made initial investments in emerging technologies are looking at how their pilot projects are paying off and where they might extend to the supply chain. They are starting to think creatively about how to combine technologies to offer a product, service, or business model not possible before.

A manufacturer will load a self-driving truck with a 3D printer capable of creating a customer’s ordered item en route to delivering it. A vendor will capture the market for a socially responsible product by allowing its customers to track the product’s production and verify that none of its subcontractors use slave labor. And a supermarket chain will win over customers by persuading them that their choice of supermarket is also a choice between being certain of what’s in their food and simply hoping that what’s on the label matches what’s inside.

At that point, a smart supply chain won’t just be a competitive edge. It will become a competitive necessity. D!

About the Authors

Gil Perez is Senior Vice President, Internet of Things and Digital Supply Chain, at SAP.

Tom Raftery is Global Vice President, Futurist, and Internet of Things Evangelist, at SAP.

Hans Thalbauer is Senior Vice President, Internet of Things and Digital Supply Chain, at SAP.

Dan Wellers is Global Lead, Digital Futures, at SAP.

Fawn Fitter is a freelance writer specializing in business and technology.

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.



The Differences Between Machine Learning And Predictive Analytics

Shaily Kumar

Many people are confused about the specifics of machine learning and predictive analytics. Although they are both centered on efficient data processing, there are many differences.

Machine learning

Machine learning is a method of computational learning underlying most artificial intelligence (AI) applications. In ML, systems or algorithms improve themselves through data experience without relying on explicit programming. ML algorithms are wide-ranging tools capable of carrying out predictions while simultaneously learning from over trillions of observations.

Machine learning is considered a modern-day extension of predictive analytics. Efficient pattern recognition and self-learning are the backbones of ML models, which automatically evolve based on changing patterns in order to enable appropriate actions.

Many companies today depend on machine learning algorithms to better understand their clients and potential revenue opportunities. Hundreds of existing and newly developed machine learning algorithms are applied to derive high-end predictions that guide real-time decisions with less reliance on human intervention.

Business application of machine learning: employee satisfaction

One common, uncomplicated, yet successful business application of machine learning is measuring real-time employee satisfaction.

Machine learning applications can be highly complex, but one that’s both simple and very useful for business is a machine learning algorithm that compares employee satisfaction ratings to salaries. Instead of plotting a predictive satisfaction curve against salary figures for various employees, as predictive analytics would suggest, the algorithm assimilates huge amounts of random training data upon entry, and the prediction results are affected by any added training data to produce real-time accuracy and more helpful predictions.

This machine learning algorithm employs self-learning and automated recalibration in response to pattern changes in the training data, making machine learning more reliable for real-time predictions than other AI concepts. Repeatedly increasing or updating the bulk of training data guarantees better predictions.

Machine learning can also be implemented in image classification and facial recognition with deep learning and neural network techniques.

Predictive analytics

Predictive analytics can be defined as the procedure of condensing huge volumes of data into information that humans can understand and use. Basic descriptive analytic techniques include averages and counts. Descriptive analytics based on obtaining information from past events has evolved into predictive analytics, which attempts to predict the future based on historical data.

This concept applies complex techniques of classical statistics, like regression and decision trees, to provide credible answers to queries such as: ‘’How exactly will my sales be influenced by a 10% increase in advertising expenditure?’’ This leads to simulations and “what-if” analyses for users to learn more.

All predictive analytics applications involve three fundamental components:

  • Data: The effectiveness of every predictive model strongly depends on the quality of the historical data it processes.
  • Statistical modeling: Includes the various statistical techniques ranging from basic to complex functions used for the derivation of meaning, insight, and inference. Regression is the most commonly used statistical technique.
  • Assumptions: The conclusions drawn from collected and analyzed data usually assume the future will follow a pattern related to the past.

Data analysis is crucial for any business en route to success, and predictive analytics can be applied in numerous ways to enhance business productivity. These include things like marketing campaign optimization, risk assessment, market analysis, and fraud detection.

Business application of predictive analytics: marketing campaign optimization

In the past, valuable marketing campaign resources were wasted by businesses using instincts alone to try to capture market niches. Today, many predictive analytic strategies help businesses identify, engage, and secure suitable markets for their services and products, driving greater efficiency into marketing campaigns.

A clear application is using visitors’ search history and usage patterns on e-commerce websites to make product recommendations. Sites like Amazon increase their chance of sales by recommending products based on specific consumer interests. Predictive analytics now plays a vital role in the marketing operations of real estate, insurance, retail, and almost every other sector.

How machine learning and predictive analytics are related

While businesses must understand the differences between machine learning and predictive analytics, it’s just as important to know how they are related. Basically, machine learning is a predictive analytics branch. Despite having similar aims and processes, there are two main differences between them:

  • Machine learning works out predictions and recalibrates models in real-time automatically after design. Meanwhile, predictive analytics works strictly on “cause” data and must be refreshed with “change” data.
  • Unlike machine learning, predictive analytics still relies on human experts to work out and test the associations between cause and outcome.

Explore machine learning applications and AI software with SAP Leonardo.


Shaily Kumar

About Shaily Kumar

Shailendra has been on a quest to help organisations make money out of data and has generated an incremental value of over one billion dollars through analytics and cognitive processes. With a global experience of more than two decades, Shailendra has worked with a myriad of Corporations, Consulting Services and Software Companies in various industries like Retail, Telecommunications, Financial Services and Travel - to help them realise incremental value hidden in zettabytes of data. He has published multiple articles in international journals about Analytics and Cognitive Solutions; and recently published “Making Money out of Data” which showcases five business stories from various industries on how successful companies make millions of dollars in incremental value using analytics. Prior to joining SAP, Shailendra was Partner / Analytics & Cognitive Leader, Asia at IBM where he drove the cognitive business across Asia. Before joining IBM, he was the Managing Director and Analytics Lead at Accenture delivering value to its clients across Australia and New Zealand. Coming from the industry, Shailendra held key Executive positions driving analytics at Woolworths and Coles in the past.