#Marketers beware: Privacy Please: How the GDPR Can Elevate Marketing

The EU’s new General Data Protection Regulation (GDPR) can be daunting, but it can have a positive impact on marketing. Here’s why.
— Read on insights.newscred.com/gdpr/

Marketing Transformation and Artificial Intelligence

Artificial Intelligence and Marketing
Artificial Intelligence and Marketing

7 examples where artificial intelligence is transforming marketing:

1. Content curation

Predictive analytics allows Netflix to optimize its recommendations. This kind of clustering algorithm is continually improving suggestions, allowing users to make the most of their subscription.

Uniting information from diverse datasets is a common use of AI.

Under Armour is one of the many companies to have worked with IBM’s Watson. The sports apparel company combines user data from its Record app with third-party data and research on fitness, nutrition etc.

The result is the ability for the brand to offer up relevant (personalized) training and lifecycle advice based on aggregated wisdom.

2. Search

In 2015, Google admitted it was using RankBrain, an AI system, to interpret a ‘very large fraction’ of search queries. RankBrain utilizes natural language processing (NLP) to help find relevance in content and queries, as well as better interpretation of voice search and user context (e.g. Google Now).

3. Predictive customer service

Knowing how a customer might get in touch and for what reason is obviously valuable information.

Not only does it allow for planning of resource (do we have enough people on the phones?) but also allows personalization of communications.

Another project being tested at USAA uses this technique. It involves an AI technology built by Saffron, now a division of Intel.

Analyzing thousands of factors allows the matching of broad patterns of customer behavior to those of individual members.

4. Ad targeting

As Andrew Ng, Chief Scientist at Baidu Research, tells Wired, “Deep learning [is] able to handle more signal for better detection of trends in user behavior. Serving ads is basically running a recommendation engine, which deep learning does well.”

Optimizing bids for advertisers, algorithms will achieve the best cost per acquisition (CPA) from the available inventory.

When it comes to targeting of programmatic ads, machine learning helps to increase the likelihood a user will click. This might be optimizing what product mix to display when retargeting, or what ad copy to use for what demographics.

5. Customer segmentation

Plugging first- and third-party data into a clustering algorithm, then using the results in a CRM or customer experience system is a burgeoning use of machine learning.

Companies such as AgilOne are allowing marketers to optimize email and website communications, continually learning from user behavior.

6. Sales forecasting

Conversion management again, but this time using inbound communication.

Much like predictive customer service, inbound emails can be analyzed and appropriate action taken based on past behaviors and conversions.

Should a response be sent, a meeting invite, an alert created, or the lead disqualified altogether? Machine learning can help with this filtering process.

7. Image recognition

Google Photos allows you to search your photos for ‘cats’. Facebook recognizes faces, as does Snapchat Face Swap.

Perhaps the most exciting implementation of image recognition is DuLight from Baidu…Designed for the visually impaired, this early prototype recognizes what is in front of the wearer and then describes it back to them.

Marketing Transformation and Artificial Intelligence

Artificial Intelligence and Marketing
Artificial Intelligence and Marketing

Here are seven examples where artificial intelligence is transforming marketing:

1. Content curation

Predictive analytics allows Netflix to optimize its recommendations. This kind of clustering algorithm is continually improving suggestions, allowing users to make the most of their subscription.

Uniting information from diverse datasets is a common use of AI.

Under Armour is one of the many companies to have worked with IBM’s Watson. The sports apparel company combines user data from its Record app with third-party data and research on fitness, nutrition etc.

The result is the ability for the brand to offer up relevant (personalized) training and lifecycle advice based on aggregated wisdom.

2. Search

In 2015, Google admitted it was using RankBrain, an AI system, to interpret a ‘very large fraction’ of search queries. RankBrain utilizes natural language processing (NLP) to help find relevance in content and queries, as well as better interpretation of voice search and user context (e.g. Google Now).

3. Predictive customer service

Knowing how a customer might get in touch and for what reason is obviously valuable information.

Not only does it allow for planning of resource (do we have enough people on the phones?) but also allows personalization of communications.

Another project being tested at USAA uses this technique. It involves an AI technology built by Saffron, now a division of Intel.

Analyzing thousands of factors allows the matching of broad patterns of customer behavior to those of individual members.

4. Ad targeting

As Andrew Ng, Chief Scientist at Baidu Research, tells Wired, “Deep learning [is] able to handle more signal for better detection of trends in user behavior. Serving ads is basically running a recommendation engine, which deep learning does well.”

Optimizing bids for advertisers, algorithms will achieve the best cost per acquisition (CPA) from the available inventory.

When it comes to targeting of programmatic ads, machine learning helps to increase the likelihood a user will click. This might be optimizing what product mix to display when retargeting, or what ad copy to use for what demographics.

5. Customer segmentation

Plugging first- and third-party data into a clustering algorithm, then using the results in a CRM or customer experience system is a burgeoning use of machine learning.

Companies such as AgilOne are allowing marketers to optimize email and website communications, continually learning from user behavior.

6. Sales forecasting

Conversion management again, but this time using inbound communication.

Much like predictive customer service, inbound emails can be analyzed and appropriate action taken based on past behaviors and conversions.

Should a response be sent, a meeting invite, an alert created, or the lead disqualified altogether? Machine learning can help with this filtering process.

7. Image recognition

Google Photos allows you to search your photos for ‘cats’. Facebook recognizes faces, as does Snapchat Face Swap.

Perhaps the most exciting implementation of image recognition is DuLight from Baidu…Designed for the visually impaired, this early prototype recognizes what is in front of the wearer and then describes it back to them.

The rise of the chief marketing technologist | IBM THINK Marketing

marketingtechnologist

Source: The rise of the chief marketing technologist – IBM THINK Marketing

This article was written by Marco Antonio Cavallo from CIO and was legally licensed through the NewsCred publisher network.

Whenever we hear the word “digitalization,” we must understand that it is the sound of inevitability and irreversibility. The digital economy isn’t on the horizon anymore, it′s here and it is here to stay. It’s no longer a secret that the digital economy is changing the world at an unprecedented rate. Companies that are looking to succeed in this fast emerging new economy must transform themselves by reinventing their business models, strategies, processes, and practices, and that impacts on the roles of all of its employees, as well as bringing departments to work together, once everyone is more and more dependent of technology to function.

It’s no surprise that marketing is rapidly becoming one of the most technology-dependent functions across all businesses. Gartner has predicted that by 2017, a company’s chief marketing officer (CMO) would be spending more on technology than its CIO, and that is becoming more credible every day, as many CMOs have adopted technology in their everyday activities, showing that technology became the core of marketing nowadays. Every year, CMOs are globally directing their budgets to the usage of technology or software in many different marketing areas.

IDC Research has released a few predictions on how marketing will strategically use technology to accelerate client acquisition, brand awareness, to gather and analyze market and customer information and even to optimize its operational efficiency in order to generate more revenue for companies and be more accurate when directing resources, mainly by enhancing customer experience.

1. In 2017, CMOs will spend more on content marketing assets than on product marketing assets: For decades, the product launch has reigned as the kingpin content event. With a “bill of materials” stretching through multiple Excel pages, product marketing assets suck up a major portion of the marketing budget – and much of that content is wasted. The days of product content dominance are numbered. Product content will remain important, but it will take its place behind the content marketing assets matched to decision-journey stages.

  1. By 2020, 50 percent of companies will use cognitive computing to automate marketing and sales interactions with customers: A few leads go right to sales. But the majority need further qualification and extended nurturing. Companies will increasingly turn to smart systems that automatically assess and respond to buyers at the point of need. IBM recently added Watson to its marketing cloud offerings. The question is not when cognitive marketing will become mainstream – but rather, will anyone notice?
  2. In 2017, 20 percent of large enterprise CMOs will consolidate their marketing technology infrastructure: Marketing has been absorbing marketing technology a bite at a time for more than a decade. Many organizations now manage dozens (if not hundreds) of point solutions. Just as marketing environments are hitting the wall of this operational complexity, marketing tech vendors are building solid integrated platforms – able to be tailored through a partner eco-system. A fortuitous convergence of supply and demand.
  3. By 2018, predictive analytics will be a standard tool for marketers, but only a third will get optimal benefit: Early adopters of predictive analytics for buyer behavior report amazing results. The benefits come from the ability to discover hidden segments that have a high propensity to buy. Marketers can also better serve these segments with behavioral targeting. However, the majority of marketers face big challenges to achieving the benefits. Chief inhibitors? Lack of statistical skills, stubborn organizational silos that won’t integrate data, and a culture that resists truth when it goes against tradition.
  4. By 2018, 50 percent of CMOs will make significant structural changes to their “intelligence” operations and organizations: “Intelligence” as a capability is growing in importance in modern marketing organizations. Intelligence includes market intelligence (MI), business intelligence (BI), competitive intelligence (CI), and social intelligence (SI). In the past, these four functions were spread around the enterprise. Now, IDC sees more companies consolidating into a larger, single, intelligence group – often combining with intelligence functions from other areas like sales. The elimination of silos in this important area is a positive sign.

With that perspective, it is clear that technology has turned a black art into hard science. Marketing now must be well versed in customer data, analytics, mobile, social and marketing automation tools, and that requires new type of executive. The Chief Marketing Technologist is emerging at the center of this transformation as a part strategist, part creative director, part technology leader, and part teacher professional. Its mission is very clear: align marketing technology with business goals, serving as a liaison to IT, and evaluating and choosing technology providers. About half are charged with helping craft new digital business models as well.

The best CMTs are able to set a technology vision for marketing in the digital age. They champion greater experimentation and more agile management of that function’s capabilities, as well as act as transformation agents, working within the function and across the company to create competitive advantage and collaboration. It is not difficult to enlist some of the main reasons why this new executive has emerged:

  • Software became the chief means of engaging prospects and customers: A marketing team’s choice of software and how to configure and operate it, along with how creatively the team applies it, materially affects how the firm perceives and influences its audience and how the audience sees the firm.
  • Digital marketing and e-commerce skills: once those two methodologies increasingly augment or replace traditional touch points, the importance of mastering those capabilities grows. Digital marketing budgets are expanding annually at double-digit rates, and CEOs say that digital marketing is now the most important technology-powered investment their firms can make.
  • The rise in digital budgets: it is not merely a migration of spending from traditional to digital media. A growing portion of marketing’s budget is now allocated to technology itself. A recent Gartner study found that 67% of marketing departments plan to increase their spending on technology-related activities over the next two years. In addition, 61% are increasing capital expenditures on technology, and 65% are increasing budgets for service providers that have technology-related offerings.
  • Efficiently manage all this technology: there are now well over 1,000 marketing software providers worldwide, with offerings ranging from major platforms for CRM, content management, and marketing automation to specialized solutions for social media management, content marketing, and customer-facing apps. Relationships with agencies and service providers now include technical interfaces for the exchange and integration of code and data. And bespoke software projects to develop unique customer experiences and new sources of advantage are proliferating under marketing’s umbrella.

The reason why this is a growing role within companies is very simple. In this new digital economy environment, the CMO and the CIO must collaborate closely, although this executive-level cooperation isn’t just enough. A supporting organizational structure is also needed and vital for this collaboration to work properly. A company can’t simply split marketing technology down the middle and declare that the CMO gets the marketing half and the CIO gets the technology half. Such division might look good on paper, but it leaves yawning knowledge gaps in practice.

Marketing might not understand how to fully leverage what IT can offer, and IT might not understand how to accurately translate marketing requirements into technical capabilities. Instead, marketing technology must be managed holistically. In a virtuous cycle, what’s possible with technology should inspire what’s desirable for marketing, and vice versa. The right structure will help marketing become proficient with the array of software it must use to attract, acquire, and retain customers. It will help marketing leadership recognize how new technologies can open up new opportunities and allow marketing to deftly handle the technical facets of agency and service provider relationships in both contract negotiations and day-to-day operations.

The chief marketing technologist role itself is already an acknowledgement of just how important the marketing group is to driving revenue within the organization and, when properly resourced, how today’s marketing information systems are driving the current and future growth of the business. Only by bringing the CIO and the CMO together can the CEO have a complete picture of what insights must be acted upon quickly in order to establish or maintain the top market position. In a nutshell, the power comes from the intersection between marketing and IT.

Today, companies can no longer afford separate silos between marketing and IT. The rapid collapse of these silos means that one person must be able to converse seamlessly between both groups. While many CMOs are getting their arms around the technology side of their business, the natural evolution of this role is for the CIO to improve its marketing skills in order to grow into the Chief Marketing Technologist role. The faster we embrace these trends, the bigger the impact we will have on our bottom line. This is the imminent future of the industry, and it’s the reason chief marketing technologists will be in high demand within 2017 and in the years to come.

Big Data Trends | Strategies driving investments in data

imgresLast year, IDG published a study 2015 Big Data and Analytics, Insights into Initiatives and Strategies Driving Data Investments that was based on interviews with 1,139 IT leaders from nine industries with high tech (16%), government (12%), financial services (11%) and manufacturing (9%) being the top four industries surveyed.

 

Key findings Infographic:

Below are a few key take-aways, the report is embedded at the bottom of this post:

  • 80% of enterprises surveyed have data-driven and big data projects in implementing or planning stages today versus 63% of SMBs. 37% of enterprises have deployed data-driven projects in the last year, and 18% are in the process of implementing or piloting projects as of today.
  • 83% of organizations prioritized structured data initiatives as critical or high priority in 2015, and 36% increased their budgets for data-driven initiatives.
  • Improving the quality of decision making (61%), improving planning and forecasting (57%) and increasing the speed of decision making (51%) are the three most common business goals and objectives driving data-driven initiatives in organizations today. The following graphic compares which business initiatives are driving big data investment and the positive impact of big data on each.
  • 36% of enterprises expect their IT budget allocations for data-driven initiatives increased in 2015, 41% anticipated budget levels would remain at current levels and 21% aren’t sure. Only 3% say data-driven and big data-related project funding will decrease.
  • Data analytics continues to accelerate as the most preferred solution for gaining greater business insight and value from data, with this category increasing in importance 55% from 2014 survey results. In enterprises, data analytics (65%), visual dashboards (47%), data mining (43%), data warehousing (40%) and data quality (39%) are the five most preferred solutions. In my discussions with CIOs in financial services and manufacturing companies, the shift away from pre-built dashboards with common metrics and key performance indicators (KPIs) to the flexibility of defining their own data models in metrics is the future. Dashboards in financial institutions need to have the flexibility of quickly integrating entire new metrics and KPIs as their business models change. For manufacturers, the need for interpreting shop floor data to financial results is what’s driving data analysis and dashboards in the many manufacturing industries adopting analytics today.
  • The number of enterprises who have deployed/implemented data-driven projects increased 125% in the last year, with 42% still planning data implementations as of today. The following graphic from the study illustrates a comparison of 2014 and 2015 plans for considering, planning and implementing data-driven projects.

 

View the report here:

Download the IDG Report: 2015 Big Data and Analytics, Insights into Initiatives and Strategies Driving Data Investments

Google paid Apple $1bn to be default iOS search engine | Technology | The Guardian

 

google-apple-650Lawsuit proceedings reveal Apple was paid handsomely to make Google default search engine on mobile Safari, while company’s total revenue from Android just $31bn…

 

Source: Google paid Apple $1bn to be default iOS search engine | Technology | The Guardian

How More Accessible Information Is Forcing B2B Sales to Adapt

jan16-05-563960997by: Andris A. Zoltners, PK Sinha, and Sally E. Lorimer

Over the past 20 years, information technology and digital channels have changed the way consumers shop for products ranging from cars to homes to electronics. Those forces are dramatically changing the way B2B companies and their customers approach buying and selling, too.

Business buyers are more connected and informed than ever before. Sellers must respond. For buyers and sellers alike, this creates complexity, anxiety, and opportunity all at the same time.

From the buyer’s perspective, information technology and digital channels provide access to information and enable self-sufficiency. When a buyer wants to learn about virtually any product or service, an internet search yields thousands (if not millions) of results, including online articles, videos, white papers, blogs, and social media posts. In addition to supplier websites that showcase specific solutions, there are likely to be online sources (ranging from the self-serving to the unbiased) to help buyers learn and compare solution alternatives. Buyers can also use self-service digital channels for new or repeat purchases and for training and support. Using information technology and digital channels, buyers can take over many steps of buying that salespeople once cherished as their source of value.

Buyers are at different levels of self-sufficiency: any single buyer can be at one level for some purchases and at a different level for others. Sometimes buyers prefer to eliminate the salesperson completely. According to one corporate technology buyer: “Our supplier’s customized self-service purchasing portal makes it easy to place reorders, track shipping, and return products hassle-free.” Other times buyers seek help from salespeople. The same corporate buyer relies on salespeople when evaluating new technologies: “It’s more efficient to work with a few trusted salespeople, compared to spending hours on my own sifting through all the information and misinformation that’s out there.”

Because of the diversity of buyer self-sufficiency, the traditional methods sellers use to customize their selling approach for customers are no longer enough. Considering factors such as customer potential and needs is still relevant. But today, customer knowledge/self-sufficiency is a growing driver of how customers want to buy. At one end of the spectrum are the “super-expert” customers, skilled in gathering information from many sources and self-sufficient in using that information to make purchase decisions. At the other end of the spectrum are the “information-seeking” customers, who want help with examining and evaluating the plethora of information. Many customers are in between these two extremes, or are at different points at different times or for different purchases.

Smart sellers match their selling approach to the customer’s level of buying knowledge and self-sufficiency. For example, when leaders at Dow Corning observed in the early 2000s that some customers wanted an easier, more affordable way to buy standard silicone products, they created Xiameter, a brand that includes thousands of less-differentiated products sold exclusively through a low-cost, no-frills, self-service online sales channel. Customers who desired a higher-touch approach could still purchase products under the Dow Corning brand name, which also includes specialty silicones backed by research and technical services.

As sellers need a more customized approach to reaching customers, they have a big arsenal of data and technology at their disposal. Systems (e.g., CRM), tools (e.g., data management, analytics), infrastructures (e.g., mobile, cloud), and information (e.g., big data) give sellers knowledge about buyers and enable sales force members to make smarter decisions. And sellers who once connected with customers primarily through personal selling can now use an array of digital communication channels to supplement or supplant face-to-face sales efforts.

Consider the impact of information technology and digital channels from the seller’s perspective. Here are examples from several industries.

  • Finding banking customers: “Social media allows us to cost-effectively reach out to more prospects and showcase our services.
  • Understanding specialty chemicals customers: “Big data and analytics help us improve customer targeting and achieve more cost-effective deployment.”
  • Acquiring advertising customers: “We now have richer demographic information to help us create more powerful sales messages, resulting in more sales.”
  • Serving and growing business logistics customers: “Our salespeople use a business review app to guide quarterly account reviews with major customers. By sharing data about performance and cost savings, these discussions enhance customer value and retention.

Information technology and digital channels can help sellers become more effective and efficient, but they can also be a source of disharmony and confusion if implemented without thought. Too many sellers have wasted millions of dollars on sales technologies such as CRM systems and data warehouses that never lived up to their potential.

Success for sellers requires many sales force changes beyond information technology and digital solutions. To start, salespeople need new competencies. Customers are no longer interested in meeting with “talking brochures,” so salespeople must do more than share product information. They must adapt to each customer’s level of knowledge and self-sufficiency. They must use email, social media, webinars, video conferencing, and other tools judiciously to maximize their own productivity and make things more efficient for buyers. They must help their companies coordinate customer outreach across multiple communication channels to ensure buyers get a well-orchestrated and consistent message.

For example, in the pharmaceutical industry, gone are the days when the majority of physician education occurred through face-to-face contact between salespeople and physicians. Companies are now tracking individual physician communication preferences and are reaching out with the combination of face-to-face visits and/or digital methods (e.g., websites, email, podcasts, virtual detailing, video conferencing, mobile apps) that best meets each physician’s needs. Salespeople need competencies as orchestrators who can ensure an effective and efficient connection.

Developing new sales force competencies is just a start. Sales leaders must also reengineer their sales forces by implementing changes across the entire range of sales force decisions: roles, size and structure, hiring, training, coaching, incentive compensation, performance management, and sales support systems.

Source: HBR: How More Accessible Information Is Forcing B2B Sales to Adapt

 

Big Data Trends | Strategies driving investments in data

IDG Enterprise logoLast year, IDG published a study 2015 Big Data and Analytics, Insights into Initiatives and Strategies Driving Data Investments that was based on interviews with 1,139 IT leaders from nine industries with high tech (16%), government (12%), financial services (11%) and manufacturing (9%) being the top four industries surveyed.

 

Key findings Infographic:

Below are a few key take-aways, the report is embedded at the bottom of this post:

  • 80% of enterprises surveyed have data-driven and big data projects in implementing or planning stages today versus 63% of SMBs. 37% of enterprises have deployed data-driven projects in the last year, and 18% are in the process of implementing or piloting projects as of today.
  • 83% of organizations prioritized structured data initiatives as critical or high priority in 2015, and 36% increased their budgets for data-driven initiatives.
  • Improving the quality of decision making (61%), improving planning and forecasting (57%) and increasing the speed of decision making (51%) are the three most common business goals and objectives driving data-driven initiatives in organizations today. The following graphic compares which business initiatives are driving big data investment and the positive impact of big data on each.
  • 36% of enterprises expect their IT budget allocations for data-driven initiatives increased in 2015, 41% anticipated budget levels would remain at current levels and 21% aren’t sure. Only 3% say data-driven and big data-related project funding will decrease.
  • Data analytics continues to accelerate as the most preferred solution for gaining greater business insight and value from data, with this category increasing in importance 55% from 2014 survey results. In enterprises, data analytics (65%), visual dashboards (47%), data mining (43%), data warehousing (40%) and data quality (39%) are the five most preferred solutions. In my discussions with CIOs in financial services and manufacturing companies, the shift away from pre-built dashboards with common metrics and key performance indicators (KPIs) to the flexibility of defining their own data models in metrics is the future. Dashboards in financial institutions need to have the flexibility of quickly integrating entire new metrics and KPIs as their business models change. For manufacturers, the need for interpreting shop floor data to financial results is what’s driving data analysis and dashboards in the many manufacturing industries adopting analytics today.
  • The number of enterprises who have deployed/implemented data-driven projects increased 125% in the last year, with 42% still planning data implementations as of today. The following graphic from the study illustrates a comparison of 2014 and 2015 plans for considering, planning and implementing data-driven projects.

 

View the report here:

Download the IDG Report: 2015 Big Data and Analytics, Insights into Initiatives and Strategies Driving Data Investments

The Best BPM Platforms for Digital Business

In the last quarter of 2015, Forrester Research identified Pegasystems, Appian, and IBM as leading the field of suppliers of business process management platforms for today’s digital business.

This post focuses on the value that Pegasystems delivers to today that is transforming how their clients engage with their customers throughout each stage of engagement.

photoSource: Pega.com The complexity of today’s business makes it hard to truly know a person across marketing, sales and service. There are too many customers, too many permutations of what they need and too many obstacles. Your customer base has grown, and so has your need for more sophisticated technology that not only understands prospect and customer demands but also helps accomplish your business objectives. Initially, your systems did what you needed: track customers and help you market and sell to them. But as your enterprise acquires companies and systems, technology becomes a barrier to how you engage with customers — across departments, time zones and geographies. Complexity has also brought inflexibility, making it hard for systems to adapt to changing needs, changing markets and changing regulations. It also makes it difficult to train employees because they’re battling systems, not servicing customers..Click here to read more.

The 8 white boarding videos that follow will help you visualize the unique value that Pega is delivering value today to their clients customer engagement management initiatives around the customer experience…

Build for Change: Directly Capture Objectives (DCO)

With Pega 7, you capture the policies and procedures that define your business – including rules, data models, UIs, integrations, reports, and organizational structures – in the model. Pega 7 automates the code generation. As the requirements change, a change in the model equates to an immediate system change.

Build for Change: Situational Layer Cake

Situational Layer Cake™ (SLC) architecture enables organizations to differentiate, specialize, and reuse their business applications. Pilot projects can grow into enterprise transformation programs overnight. Instant reuse dramatically accelerates the time to value for organizations seeking to be more agile in response to changing market and regulatory demands.

Build for Change: Case Lifecycle Management™

When a business person starts explaining their needs for an enterprise, they don’t generally dive into process details. And they certainly don’t describe “transactions.” They think in terms of the case and its stages. Rather than drawing an end-to-end process, Pega 7 provides tools for business people to define the major steps of how work gets done – essentially building the skeleton on which you hang the more detailed process. You establish a business view of the data before debating the details.

Build for Change: Mashup

Traditional service or API-based architectures result in hard-coding the UX logic into each channel independently. Process changes must therefore be made in multiple places, making it impossible to deliver a consistent customer experience. By embedding the Pega UX directly into the mobile or web channels, all of the intelligence and capability of Pega 7’s Case Management is brought directly to the customer touchpoint.

Build For Change: Omni-Channel UX

Pega’s Omni-Channel UX delivers an optimized and consistent user experience in every channel. Learn more at http://www.pega.com/platform

Build For Change: Event Strategy Manager

Pega’s Event Strategy Manager gives you the tools you need to turn streams of customer data into valuable business decisions and actions. Learn more at http://www.pega.com/platform

Build for Change: Pega Live Data

Pega Live Data allows users to quickly and easily define the data required to build the apps they need, and then access that data in their running application – all without having to worry about how and where the data is actually stored and accessed.

Build for Change: Next Best Action

The real value from Big Data and analytics comes when every customer conversation delivers exactly the right message, the right offer, and the right level of service to both give the customer a great experience and maximize the customer’s value to the organization. With Pega’s Next Best Action, business experts develop decision strategies that combine predictive analytics,
adaptive analytics, traditional business rules.

 

The Forrester Wave™: BPM Platforms For Digital Business, Q4 2015

Key Takeaways: Pegasystems, IBM, and Appian lead the pack

Forrester’s research uncovered a market in which Pegasystems, Appian, and IBM continue to lead the pack. Software AG, Oracle, Newgen Software, OpenText, Bizagi, K2, and DST Systems offer competitive options. Red Hat and TIBCO Software lag behind. The BPM Platforms Market Is Growing As EA Pros Accelerate Digital Transformation The BPM platforms market is growing because more EA professionals see BPM as a way to address emerging challenges for customer experience and digital business. This market growth is, in large part, because EA pros increasingly trust BPM platform providers to act as strategic partners, helping them transform how they use technology to win, serve, and retain customers in the digital age. Differentiators Include Rapid Development, UX Design, And Case Management As legacy BPM technology becomes outdated and less effective, improved delivery speed and process flexibility will dictate which providers will lead the pack. Vendors that can provide fast ramp-up, flexible mobile experiences, and dynamic case management position themselves successfully to deliver speed and business agility to their customers.

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The Importance Of Asking Questions | Ogilvydo.com

“He who asks a question is a fool for five minutes; he who does not ask a question remains a fool forever” – Chinese proverb.

What’s the one thing that the world’s leading innovators share with children? They both learn through asking questions. It’s the simplest and most effective way of learning. Yet somehow we have forgotten this lesson as we get older. We just don’t value questioning as much as we should.

Not asking good or even enough questions has a direct impact on the quality of choices you make. Habituating the art of asking questions enables you to gain deep insight, develop more innovative solutions and to arrive at better decision-making.

Brilliant thinkers and scientists never stop asking questions. “Asking questions is the single most important habit for innovative thinkers,” says Paul Sloane, the UK’s top leadership speaker on innovation.

  • Newton: “Why does an apple fall from a tree but, why does the moon not fall into the Earth?”
  • Darwin: “Why do the Galapagos Islands have so many species not found elsewhere?”
  • Einstein: “What would the universe look like if I rode through it on a beam of light?”


Asking these kinds of basic questions started the process that led to their great breakthroughs. And asking questions is as relevant today. Only by constantly asking why can you find better products. In his book “A More Beautiful Question: The Power of Inquiry to Spark Breakthrough Ideas”, Warren Berger cited the example of Edwin H. Land, who invented the Polaroid camera in response to his 3 year old daughter asking why the camera that they used couldn’t produce a photo immediately. There are plenty of other cases; Airbnb exists as a response to the question “why should you be stuck without a bed if I’ve got an extra air mattress?”

The list is endless, as many companies and even entire industries can be traced back to a single question.

How do we master the art and science of asking effective questions and how do we make it a habit?

  1. Create an environment where curiosity is welcomed and rewarded.
  2. Become a keen observer of everything you see, hear and experience.
  3. Look at the world with fresh eyes, question the familiar, assume nothing is obvious.
  4. Understand the power of different types of questions – how they should be used and when.
  5. Keep asking why till you can go no further.

“Good questioning should stimulate, provoke, inform and inspire” says Sloane, while Berger feels it can “help us learn, explore the unknown and adapt to change”. What could be a great question that could shift the way you or your organisation perceive or think about something that has the potential to act as a catalyst for change?

Source: The Importance Of Asking Questions | ogilvydo.com