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.

Marketing and Artificial Intelligence

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.

Data Driven V. Predictive Marketing: BEWARE JETSON’S MARKETING!

The Big Willowby: Charlie Tarzian

My son came to me one day in early December and said:  ‘Hey, Dad, let’s get Mom one of those robotic vacuum cleaners.  You know, the ones you switch on and they vacuum your whole floor!’  He could not contain his enthusiasm – this was going to be great – no one would have to vacuum our floors ever again!!!

So we went to Amazon (of course) and two days later our round disc of a maid showed up via FEDEX.

Come Christmas Day, the robot fully charged, off we went to the kitchen to marvel at what was certain to be a life changing event.  We turned it on and put it down on the floor and the vacuum swung into action.  It crossed the floor, sensed it was coming to a wall, made a pivot, chugged in another direction…and got stuck on the slight incline by the fireplace…then stuck again on the floor mat by the stove…then got caught between a chair and a table and went into a break dance that would make R2D2 jealous.

I bring this up because a colleague sent me this little snippet from the website of a Predictive Marketing vendor:

“Predictive Marketing doesn’t need to be a services heavy engagement to get you up and running. With CompanyX (name of company withheld) and our push button integration, we can integrate with your existing systems and build your predictive model in under a day. – See more at: http://www.companyx.com/what-we-offer/#sthash.vBzkU18n.dpuf

There you have it: Jetson’s Marketing – just push our one little button and off you go:  great leads, great meetings, great website experiences – in fact all your marketing/sales problems solved in ‘under a day’.  All that is left to do is fire your staff, except for that one person in charge of pushing the button when you run out of leads, meetings and website visitors.

Look, I know what I don’t know, but I can tell you this: whatever you’re thinking the new generation of transformative marketing is – one thing it isn’t is automated bliss.  It takes a fair sized village to make things happen.  And herein lies the huge disconnect between data driven marketers and the shiny new object called Predictive Marketing.  Data driven marketers know that data can and should be utilized across the marketing/sales continuum – but it is more about data orchestration than anything else.  Therefore, one button, add water and stir does not take into consideration any of the cause and effect across all the communications and transactive channels that marketers rely on.

Marketing is services heavy (sorry, Company X) because at the nexus of MarTech, AdTech and Sales Enablement sits quite a bit of cause and effect.  And unless you aspire and build towards using predictive data to positively impact all channels aligning as one – then what you are predicting is a very small sliver of what could be.  In other words, if the connectivity and synapsis among outward facing channels are not orchestrated and optimized using predictive data and you are not feeling good that all channels are working in sync – then how can you predict a scaled outcome?  The predictions you are making will reflect a small percentage of the whole – and so instead of widening your funnel and increasing your opportunities along every step in a buying journey, you are narrowing that funnel based on a flawed assumption that you are predicting against a full boat of reliable data.

On the other hand, Data Driven Marketing  sets up to be based on solving for the cause and effect of what is less than optimized (can anyone say, broken?)  It attempts to determine (not predict) what works and doesn’t and then – as a village – cohesively knits together a response to results that can be repeatable but certainly is not a just add water, one button pushed result.

So – are we starting to see a difference:  Predictive Marketing – a push button approach to a complicated set of executional events and response, or, Data Driven Marketing – a human driven (sorry robots!) approach to the cause and effect of humans communicating to other humans about things that may or may not be important to the recipient (we always hope for the former)?

What do you think?  We would love to know.  Have any stories to share – we would love to hear from you.

by: Charlie Tarzian, Founder, The Big Willow

Inside The Growing Social Media Skills Gap – FastCompany

Fast Company LogoBY RYAN HOLMES

On February 4, 2004, a handful of Harvard students logged onto a newly launched website called thefacebook.com. Just a dozen years later, some 2 billion people—nearly a third of the planet’s population—are social media users.

So if companies are having trouble keeping up with that pace of adoption, it’s no surprise. Businesses have overcome their earlier skepticism and raced head-on into the social arena, chasing the estimated three-quarters of consumers who now say social media influences their buying decisions. Nearly 90% of U.S. companies are currently using Twitter, Facebook, and other networks—all jockeying for their share of the estimated $1.3 trillion in value that social media stands to unlock.

There’s just one small problem: The contemporary workforce is woefully ill-equipped to help companies unlock it.

THE SKILLS GAP YOU HAVEN’T HEARD OF

While social media races ahead, formal training and education programs are lagging seriously behind. If that isn’t making headlines, it’s testament to social media’s comprehensive mainstreaming: “Facebook? I use that everyday. Who needs to be trained in it?”

Yet a meager 12% of the 2,100 companies in a 2010 Harvard Business Review survey said they’re using social media effectively. And more recent research by Capgemini and others show that confidence gaining only incrementally.

IN A SHORT TIME . . . SOCIAL MEDIA DUTIES HAVE BEEN RADICALLY DEMOCRATIZED AND DECENTRALIZED [WITHIN COMPANIES].

Reports of social media gaffes and blunders in the workplace are still routine. Meanwhile, the real price of the skills gap often goes unnoticed—billions of dollars in missed opportunities and lost revenue.WHAT’S BEHIND THE SHORTFALL

The clearest culprit is the breakneck proliferation of new platforms and features. Around a year ago, Snapchat was still a toy for teens to trade disappearing messaging; today it’s the latest way to reach young customers on their own turf. As more platforms incorporate more sophisticated features, even the most plugged-in users are struggling to keep up.

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At the same time, how social media is used in the workplace is fundamentally changing. Just a few years ago, social media in the office was the domain of specialized social media managers, the gatekeepers who owned a company’s public face on the leading platforms. In a short time, however, social media duties have been radically democratized and decentralized. The number of job descriptions on Indeed.com mentioning social media skills is booming: “[We’re] seeing this demand span many levels, from executive assistants to senior vice presidents,” Amy Crow, Indeed’s then communication director told Quartz a few years ago.

Since then, employees have been asked to use social media in ever more numerous and unfamiliar ways. The standard marketing functions are just the tip of the iceberg. Social tools are being used to streamline customer service, drive sales, improve HR processes, and build employee brand advocacy programs.

Meanwhile, platforms like Facebook at Work (in beta now and expected to roll out this year) and Slack (which boasts millions of users, from NASA to your corner coffee shop) are quickly changing how workers collaborate. By bringing social messaging inside the office, these technologies are breaking down silos and boosting productivity (although some disagree). Social media is no longer a discrete thing that certain people do in certain jobs, and more of an integral component of work itself.

BECAUSE SOMEBODY GROWS UP BEING A SOCIAL MEDIA NATIVE, IT DOESN’T MAKE THEM AN EXPERT IN USING SOCIAL MEDIA AT WORK.

But this approach only works if employees are on board and up to speed. “The real problem is that we expect people to know these skills without providing any training,” William Ward, professor of social media at Syracuse University, recently told me. Social media know-how isn’t something you just pick up as a casual user. And it isn’t just older employees who are in the dark—millennial hires need training, too.”

Because somebody grows up being a social media native, it doesn’t make them an expert in using social media at work,” Ward says. “That’s like saying, ‘I grew up with a fax machine, so that makes me an expert in business.’”

BRIDGING THE SOCIAL GAP

Fixing this social skills gap is no small task. In the long term, social media coursework is slowly being incorporated into university programs, and not just for students pursuing marketing and communications degrees. Here at Hootsuite, for instance, we’ve developed a social media syllabus that’s now being used in more than 400 universities around the world by 30,000 students. Programs like these offer a foundation of social media skills for the workplace and may one day be as commonplace as introductory college writing and computer skills classes.

But what about employees struggling right now with the growing demands of social business? The good news is that companies are beginning to acknowledge social media literacy as a critical job skill (just like Internet and basic computer literacy back in the day) and are starting to offer on-the-job training programs. Altimeter reports that almost half of the companies it surveyed are planning on rolling out some kind of internal social education program for employees, while overall spending on corporate training is on a serious upswing, rising 15% in the U.S. in a recent year to $70 billion.

The challenge, of course, is how to teach social media in such a mercurial environment. In the last year alone, for instance, we’ve seen the meteoric rise of “social video” and a whole new crop of one-to-one messaging apps, while Twitter has struggled to reinvent itself.

But few employees have time for in-depth courses or bootcamps. Ultimately, the right training solution needs to be on-demand and mobile-friendly. Currently, some of the bestpaid options are coming not from traditional educational sources, but from companies immersed in the social and digital media space, offering real lessons from the front lines. (Hootsuite’s own online course, Podium, is one free alternative, with 50,000 users and counting.)

TWITTER, FACEBOOK, INSTAGRAM, AND OTHER NETWORKS AREN’T GOING AWAY . . . [AND] SOCIAL MEDIA BUDGETS AT COMPANIES ARE EXPECTED TO DOUBLE IN THE NEXT FIVE YEARS.

Ultimately, though, any investment in upgrading social media skills in the workplace is likely to be money well spent. Twitter, Facebook, Instagram, and other networks aren’t going away. Social business has become business as usual. Indeed, social media budgets at companies are expected to double in the next five years.

To avoid throwing good money after bad, companies need to ensure that their employees actually know how to use new and emerging social technologies. Those that succeed in closing the social media skills gap will discover new ways to reach and retain customers, engage and recruit employees, and boost productivity. Those that fail will miss out on their chunk of a multitrillion-dollar pie, and might not be around long enough to regret it.

CMO Council: Marketers are struggling with Customer Engagement – Thunderhead

imgresBlog summarizing the CMO Council new report on the good, the bad and the ugly of how marketers feel they are coping with improving customer engagement

Source: CMO Council: Marketers are struggling with Customer Engagement – Thunderhead

The Sales and Marketing Promance (technology not included)

Many businesses lack strong alignment between their sales and marketing organizations. Whether you agree or disagree, it’s important to understand the barriers that prevent alignment. Six common barriers include:

  1. Success in the sales and marketing departments is being measured differently.
  2. Sales and marketing have a different vision of the ideal target customer.
  3. Actionable customer insight sits in disconnected databases.
  4. There is a lack of view of customers and their buying preferences.
  5. Broken processes make it impossible to track what is working.
  6. The technology is too hard to use so that there is limited adoption.

 

These barriers lead to the disconnect and are making it difficult for organizations to make the most of their sales opportunities and go to market investments. As an example, companies are unable to provide the right offers to the right people, at the right time, because customer insights live in disparate locations and the company’s go-to-market strategies are uncoordinated and inefficient.

To address this disconnect, businesses are turning to applications and new technology to help build cohesive sales and marketing alliances. The common mistake businesses have been making in their rush to technology is that they forget to address their people and process challenges first.

The promises of the digital revolution and emerging technologies are often not in line with management’s expectations. Many mid to large sized companies have rushed to replace older systems that worked, to new and unproven cloud based technologies that are not living up to expectations. Many of these decisions were based on unrealistic, pie-in the sky, cloud in the sky promises (no pun intended) and the pain is just beginning to be felt by customers.

The reality is that many companies launched into cloud based technologies without a good business plan. So perhaps 2015 will be the year many companies awaken to a reality check.

The pendulum is about to swing in another direction. Brace yourselves.

Good times ahead.

Cheers,

rvargas@solomonconsult.com

LinkedIn Cheat Sheet | Improve your profile

Increasing your visibility and building your network LinkedIn may require a few tweaks to your profile…

From how to frame your LinkedIn profile photo, what words to avoid, and the ideal number of LinkedIn connections to have through to how you can get more recommendations, here is the cheat sheet that can help you build a profile that stands out…

Europe’s Top Digital-Privacy Watchdog Zeros In on U.S. Tech Giants – The New York Times

NY TimesPARIS — The latest standoff between Europe and American tech companies runs through a quiet street just north of the Louvre Museum, past chic cafes and part of the French national library, to the ornate office of Isabelle Falque-Pierrotin.

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From here, Ms. Falque-Pierrotin has emerged as one of the most important watchdogs for how companies like Facebook and Google handle the billions of digital bits of personal data — like names, dates and contacts — routinely collected on Europeans. Since 2011, she has been France’s top privacy regulator, and for the last two years, she has led a group of European data-protection officials. In those posts, Ms. Falque-Pierrotin has regularly agitated companies to better safeguard people’s data.

Her role will come into even sharper focus in the coming weeks. Ms. Falque-Pierrotin, empowered by Europe’s highest court, will be at the heart of efforts to police how digital data is transferred outside of the European Union, a central aspect of many European and American businesses. That role will be amplified even further if, as is now widely expected, American and European negotiators fail to reach a new data-transferring deal by Feb.

Read more: Europe’s Top Digital-Privacy Watchdog Zeros In on U.S. Tech Giants – The New York Times