DISCLAIMER: I have no inside knowledge into what may or already have been discussed, or data analyzed by either AMC Theaters or MoviePass. This article is purely based on my thoughts as a movie-goer, marketer, and product manager.
“AMC Theatres has threatened MoviePass with a lawsuit, less than a day after the subscription cinema service dropped its subscription fees to $9.95 a month, reports Variety. That means subscribers are able to watch one movie every day for a month for only $9.95. MoviePass would still have to pay AMC full ticket prices each time someone uses the subscription, though. An average ticket is priced at $9.33, so a subscriber would only need to attend two movies a month to put MoviePass at a loss.
In 2016, the service started at $15 per month and ran up to $50 per month for unlimited movies in bigger cities. AMC, which is the largest theater chain in the US said in a statement that MoviePass’ model is unsustainable. The company argued that ticket prices below $10 a month over time wouldn’t be able to generate enough cash to operate quality theaters, nor produce enough income that would allow film makers to make movies of value.” – Source The Verge
I never knew about MoviePass as a subscription for unlimited movies. As a father of twins my wife and I barely get to go to the movies but once every 2 months, and it costs us an extra $100 in babysitting to go, and there’s nothing really compelling as far as “good” movies in our opinion, but I digress! Moviepass’ offer of $9.95 a month does seem to be very compelling, and ultimately very disruptive.
My first reaction in seeing that AMC is suing MoviePass for this action is to wonder out loud whether AMC had gone to MoviePass and offered to jointly analyze their respective datasets in order to see if there might be synergies in such an action.
An Outsiders Product Manager’s Perspective:
Showtimes of movies (beyond opening week of new blockbusters) are rarely full, meaning there is unused inventory in every single time slot
Pricing strategies to try and fill these slots don’t appear to have changed much beyond off peak time discounted ticket offers
Loyalty and rewards programs have now started to become more prevalent so efforts are ongoing to capture consumer profiles
Concession sales per customer are lucrative with a large popcorn and drink often costing more than the standard ticket (letting MoviePass fill shows to capacity could yield more in concession revenues than tickets itself)
Clearly I would need more data to find patterns and analyze this information to form the right conclusions. The steps would be to:
Form a Reliable Data foundation – leading to a 360-degree view of the consumer/movie-goer profile, with demographics, attribution, captured in part through AMC’s loyalty programs, but also could then be cross-referenced (Matched and Merged) with MoviePass’ subscribers to enrich both data sets.
Benefit from Commercial graph technology to find friends and family affiliations to drive offers (see marketing perspective later) to make it more of a social/group movie-going experience
Generate Relevant Insights – by bringing together the transactions processed via the tickets bought through MoviePass vs. walk-ins, and other avenues such as Fandango, promotions etc. Stanalone Master Data Management profiles are insufficient as the real valuable insights are in the transactions/behaviors exhibited by those movie-goers, and they need to be analyzed and seamlessly aggregated back into the master profiles for marketing segmentation
Deliver Recommended Actions – So marketing teams can jointly highlight how AMC and MoviePass could gain synergies from the increased traffic to theaters. Applying machine learning and data science to the reliable data foundation, not just at a macro-level, but to generate the right programs that can take advantage of the identified profiles, to drive more personalized experiences, and revenue-generating concession sales
Leverage Data as a Service – to securely share insights between AMC and MoviePass, preserve consumer privacy, and to bring in more data from suppliers of concessions to negotiate discounts and for synergies such as just-in-time ordering to improve margins
An Outsiders Marketing Perspective:
Once all this data is aggregated, made reliable, and analyzed, the joint market teams of AMC and MoviePass could work on promotions and programs using data-driven applications. With a Modern Data Management foundation they would be able to correlate Recommended Actions back to actual outcomes. Personalizing and improving customer experiences are just the cusp of benefits that can be realized. New business models that could easily be supported might include:
Making it more of a social experience –convert real-estate into Starbucks-like hangouts, with good coffee, wireless, and a place to meet. Offer better higher-end desserts so people come 30 mins before the movie with family and friends after dinner, or stay afterwards to chat about the movie and what they thought about it
Increased kids focus – more tie-ins and kids activities, pre- and post-movie with merchandise sales in a movie “store” with branded items tied-ins. Sales immediately after the event for instant gratification is the a way to command a premium over online sales and their lower prices
Given the fact that VOD, Netflix, Virtual, and Augmented Reality are literally right in the face of and challenging the movie theater going experience, AMC and other theater operators face being disrupted. A Modern Data Management Platform as a Service is essential to not only improve revenue, margins and partner better, but possibly survive.
How do you think the experience could be improved as a movie-goer?
As a Product Manager, how would you use data to gain better insights and possibly partner better. Have you used shared data and insights in similar situations between partners, or perhaps in M&A scenarios? Please share.
As the Chief Product Officer at Reltio, my focus is on the data, and helping companies avoid being “Amazoned” (Informal definition: Brick and mortar stores under threat from online competitors). Rewind 1.5 years ago, an article by Phil Wainewright of Diginomica caught my attention. “Whole Foods Market teams with Infor to transform retail.” Credit Whole Foods executive vice president and CIO Jason Buechel with his vision to be more data-driven, and to create one source of the truth.
Whole Foods and Infor’s partnership was supposed to result in a next generation, cloud-based retail management system to transform its core operations. Infor, which hosts the software on Amazon Web Services (AWS), intended to make the capability available other retailers in the industry.
In the article, Buechel also told author Phil Wainewright of Diginomica that Whole Foods has carefully weighed the pros and cons of that cloud infrastructure being operated by Amazon Web Services (AWS), which is part of a company with which it competes in the online grocery market.
Kudos to Phil Wainewright for this article, because it called out what all Retailers are thinking today. The only way to avoid being “Amazoned” is to run on the very platform, Amazon Web Services (AWS), that can allow me to compete with Amazon.
Retailing executives are asking themselves am I okay with that? What are my alternatives? Clearly Whole Foods CIO Jason Buechel knew it was a risk worth taking. He may not have foreseen that Amazon would acquire Whole Foods, but he definitely knew that doing nothing was not acceptable.
As for the question, did Amazon buy Whole Foods for the groceries or the data? Clearly this is an amazing twofer. They get a physical presence that can help their delivery and Amazon Fresh efforts, but they also get the significant dataset of customers who buy groceries from Whole Foods. They now have the information to bring together a complete single view of the customer, from brick and mortar shopping to online purchases.
In the end, the data-driven takeaway to all retailers is not just evolve or be Amazoned, but do it fast because no company can afford to spend years working on digital transformation, when their very survival depends on better customer experience, better marketing, better omnichannel engagement, personalization and more.
Kudos to Leandro DalleMule and Thomas H. Davenport for such an excellent piece of work. The following is a brief summary of the article (with copyright attribution to HBR and the authors), with my perspective on how it ties into today’s Modern Data Management platforms.
The article makes a compelling case for a framework for thinking about two forms of data strategy categorized as “defense” and “offense.”
If you’re familiar with the concept of Master Data Management (often acronymed as MDM), and have been unsuccessfully using legacy MDM tools to aid in your overall data management strategy, the quote above might strike a nerve.
Legacy MDM over the years has been inherently flawed in that the focus on just managing “Master” data through IT governance and practices, not only misses the point of ultimate value to the end business user. The paragraph in the article continues:
The perspective of the authors is one which we at Reltio are hearing more and more:
Companies want a flexible architecture that can do both to have “single and multiple versions of the truth to support a defensive-offensive approach to data strategy.”
Source: “What’s your data strategy?” HBR May-June 2017
What exactly does this mean? SSOT is what you would expect to obtain from a legacy MDM tool if all goes well and everyone agrees and is able to obtain all of the sources that have to be blended together to create such a construct.
The problem with legacy MDM approaches is that it has not been able to keep up with the increasing number of inputs and sources across the enterprise, which ultimately require a continues redesign and rethinking of data models that are tightly coupled with how the data is stored, largely in relational database constructs.
Furthermore, legacy MDM has not kept pace with the “big data” labels of volume, velocity and variety of data that needs to be managed and understood by tools which have to be supported by “humans” in the form of data stewards, who continuously have to adjudicate and verify “matches” that are not automatically reconcilable. Additionally a full 360-degree view now is expected to include interactions and transactions, and not just the master data.
Once an SSOT is created, end business users have had a hard time getting personalized relevant insights from this accurate but vast sets of unrelated data. Leaving them having to create their own “versions of the truth” in order to achieve their unique business goals.
Fundamentally as the authors clearly state:
The article gives excellent examples of companies who have needed to either focus more on defense or offense, and where typically you would lie on the spectrum.
It even offers a set of diagnostic questions you can use to “Assess Your Strategy Position”.
The article concludes with these sage words of advice:
We whole heartedly agree that no one technology can replace the need for a “well-run data management function” but we believe that a Modern Data Management Platform as a Service (PaaS) that was architected from the ground-up to effectively support all of the capabilities discussed in this HBR article is a great foundation for most enterprises.
At Reltio we focus on Reliable Data at scale for “defense” and unlike other legacy MDM platforms, deliver Relevant Insights for “offense” from complete contextual 360-degree views, for personalized engagement, with not just the business users of our customers, but ultimately for their end customers as well.
And just as the authors elude, to machine learning needs to provide the Recommended Actions that not only help with SSOT, but the creation of MVOT to drive business impact.
Please let me know your thoughts about the excellent HBR article, and my use of a gratuitous puppies in Warriors uniform click-bait photo. There is a tie-in though, the Golden State Warriors are good at both Offense and Defense 🙂
A Sneak Peek into DataDriven17: The Modern Data Management Summit
Last week Reltio hosted the inaugural Modern Data Management Summit. The event was held in the bustling Union Square neighborhood of San Francisco. The idea of this event germinated from the need that modern businesses, with evolving business models, are searching for newer ways to capitalize on their data assets.
The cross-industry participation from life science, healthcare, media, high technology, automotive, financial services, and consulting gave participants an opportunity to learn from best practices outside their market. With over 40 sessions in two days, the event was a cornucopia of knowledge.
The event was kicked off by Ramon Chen, CMO and Chairperson for the summit. He was followed by Manish Sood, Founder and CEO, who gave an electric keynote on what it means to be truly data-driven.
Strategies to improve commercial effectiveness in life sciences
Insights-driven customer and patient engagement in healthcare
Democratization of MDM helping pre-commercial companies with faster product launches
Innovative approaches to data governance in healthcare
Marketing and selling strategies of healthcare services
Collaborative approaches to better data stewardship
Real-time data enrichment with data as a service
The cross-industry track featured a terrific lineup of industry leaders who had successfully built and managed data management organizations. With standing room only in many sessions, it was evident that our guest speakers had topics that touched a chord with many attendees. Topics ranged from the role of CDO to the impact of the Blockchain. Discussion ranged from customer insights and account 360 management with Dun & Bradstreet data enrichment to discussing machine learning and predictive analytics in Cassandra, Apache Spark, and the S3 environment. Speakers reviewed data management strategies and best practices that included practitioner’s view into how to build a Bigdata platform and move to modern data integration in the cloud. With so many interesting topics and active attendee participation, there was never a dull moment.
Nasry Angel, Researcher at Forrester Research, discussed “What You Need To Go From Data Rich To Insights Driven” and Derek Strauss, former CDO at TD Ameritrade, shared how to empower the office of CDO with the Seven Streams Approach™. Building data-driven applications at a big data scale was another widely-discussed topic at sessions and panels. Dan Avilla — Director, Data Management at Hewlett Packard shared his thoughts and best practices in his session “Modern Data Management at Scale in the Cloud.”
There were many other noteworthy sessions but rather than listing all here, please fill in your information to request access to the recordings as they become available.
During discussions with various attendees, presenters, and panelist if I have to pick the top five takeaways, they will be as follows:
New business needs newer ways to manage data. The original tools and methods are not sufficient.
Before diving into data management initiatives, be clear about the objective, business purpose and desired outcomes
Master Data and analytics can no longer be kept separated, closed loop between operational applications, master data, and analytics is essential for informed decision making
Cloud brings data management to the masses and with faster time to value and no worries about over or under investment, it is the lowest risk pathway to leverage your data assets
Collaboration and data governance is crucial for success of any data management program
Sorry we missed you this year. Use the form below to request the recordings of selected sessions and to request an invitation to #DataDriven18.
Hopefully, we will see you next year at #DataDriven18 for an event bigger and better Modern Data Management Summit!
It’s no surprise this issue is #1, alignment between IT and business is a recurring challenge. Why? Because IT has to grapple with backend tools and infrastructure, while business cares about rapid access to the data to make informed decisions. Business often views IT investments in big data Hadoop as “franken-projects” that don’t correlate to the problems that need to be addressed today.
A platform that combines a modern data management Platform as a Service (PaaS) that seamlessly delivers frontline business facing applications can help. This ensures that the technology is enabling fast time to value with both teams “pulling on the same rope” to achieve company goals.
#2. Security and Privacy
Security and privacy continues to be front and center. With an increasingly digital economy, the age of social media, and stringent data management regulations, which are different based on industry and geography.
A modern data management PaaS will provide the highest level of compliance and data governance. Enabling IT to maintain access to data by role and business goals, down to the attribute-level. A detailed audit log tracks not only modifications and access to data, but even search terms and parameters. For CIOs who are concerned about public cloud providers, such as Amazon Web Services, who host modern PaaS technology, are proven and relied upon by the CIA.
#3. Speed of IT Delivery and Time to Market
The billions of dollars spent by LOB teams on self-service data preparation, self-service business intelligence, and outsourced “as-a-service insights and intelligence” reflect a desire to shortcut IT projects are typically measured in months and years, not days and weeks.
A 100% cloud PaaS ensuring agility through IaaS (Infrastructure as a Service) partners, such as Amazon Web Services has built-in Daas (Data as a Service) to rapidly onboard and blend data across all sources. Ultimately resulting in SaaS data-driven applications that deliver information into the hands of users at the speed of business, optimizing time to value.
No CIO has ever said “no thanks” to innovation. The problem lies in the legacy infrastructure which acts as a resource and budget anchor, preventing innovation. Even when budget is available, the onslaught of new technologies (witness the never ending spawning of Apache open source projects) makes new initiatives obsolete even before POCs have been completed.
Modern PaaS incorporates the latest NoSQL, big data, analytics and machine learning technologies such as Apache Cassandra, Spark and ElasticSearch. A metadata foundation supports the logical definition of the business, unconstrained by physical storage and implementation. In effect, a modern PaaS acts as a technology portfolio manager, swapping out the latest in innovative technologies when they mature. Ensuring that CIOs never have to fund those random Hadoop research projects again.
#5. Business Productivity & Efficiency
How can IT support business productivity and efficiency when many IT teams don’t fully understand the use of data once it reaches the hands of the frontline business user? IT’s focus has long been to ensure the security, management, and governance of the data. Data quality and reliability is a fundamental need that impacts business and an area in which IT and business must collaborate because only business truly understands the data, and whether it is comprehensive, and of high enough quality to improve operational execution and decision making.
A modern PaaS is rooted on a foundation of master data management (MDM) process and discipline. The best PaaS technology providers are also ranked as leaders in the Forrester Wave for MDM delivering not only in current offering and vision, but in delivering the highest business value and context.
#6. IT Value Proposition to the Business
Those not in the CIO shoes might think that this is the same as “#1 Alignment of IT to the business”. But this important topic of concern is around not just the types of projects that IT executes on, but ultimately the ROI delivered, as measured by business outcomes. CIOs are in between a rock and a hard place because today’s tools and platforms start and end with IT specific measures as regards to ROI (e.g. reduction in skilled IT experts, faster data loads, better performance). There has not been a way to accurately correlate IT investment to business outcomes … until now.
Combining both an IT data management PaaS – that is able to track the sourcing, lineage and consumption history of every attribute of every record – with the seamless integration and delivery of data-driven applications – in which business users leverage the same data to make business decisions and take action – is the ultimate solution. It gives IT teams full visibility and metrication of business outcomes. For the first time, IT and business can close the loop on ROI, directly recognizing the value IT brings to the table.
#7. IT Agility & Flexibility
Cloud embodies how CIOs can be more agile and flexible. Eliminating heavyweight, expensive to install and maintain on-premises hardware and software is critical. As processing power and the cost of storage keeps falling, companies who are handcuffed to massive CAPEX investments are unable to pivot when business needs inevitably change. The use of legacy on-premises software, upon which 12 to 18 month upgrade versions to receive new functionality also prevents any timely innovative competitive advantage.
They key is not just 100% cloud, but multi-tenant cloud. Like Salesforce.com and other innovative public cloud providers, multi-tenant Cloud delivers no impact upgrades 3 times a year. This not only provides the latest technology and features (see #4. Innovation) as soon as it becomes mature and viable, but dramatically eliminates the hidden costs of upgrade of on-premises or managed services/hosted solutions masquerading as cloud offerings. Even with unlimited financial flexibility for upgrades, the pain of on-premises hardware and software upgrade cycles comes from missed opportunities when resources are tied up simply moving from one version to another in an endless cycle.
#8. IT Cost Reduction & Controls
Cloud again helps here, this time in the form of OPEX. The ability to dial-up and more importantly dial-down storage, processing and other costs, ensures that IT can spend what it needs to and not a penny more. Shedding “over procuremen-titus” is great, but savings can also come from consolidation of IT investments in large enterprises, across divisions. This however requires significant coordination and collaboration between teams, and the elimination of “Shadow IT“.
Meanwhile the dramatic reduction in the cost of devices is now juxtaposed with the consumerization of IT, with business users demanding BYOD (Bring your own device) options. This is a security risk as well as a costly endeavor to ensure that applications run consistently on different variations of devices (mobile and PC), and versions of operating systems.
Using built-in Data as a Service can dramatically lower the cost of data acquisition from third party vendors. It can be used as a “clearing-house” to manage and monitor the consumption of data across groups, eliminating redundant data purchases. Data-driven applications can be delivered via industry standard HTML5 form, enabling embedding in existing interfaces and full compatibility with all browsers, again dramatically reducing development and support costs.
#9. Business Agility & Flexibility
The best way for IT to support business agility and flexibility is to bring together reliable data, relevant insights, and to have data-driven applications increase the speed and accuracy of actions taken by frontline business users, as business conditions fluctuate. Unfortunately today’s applications are siloed and process-driven. Focusing on a single group (e.g. CRM for sales, Marketing Automation for marketing), and there is little collaboration across teams. An isolated problem solving focus results in siloed data, which in turn necessitates yet more technology to blend and manage data to form an elusive customer or product 360-degree view.
Eliminating data silos should be a mission for all CIOs. By bringing together data across the enterprise, with MDM rigor for reliable data quality, personalized contextual relevant insights, and machine learning formulated recommended actions can help business teams be more agile. A single pool of information managed at big data scale, from a modern PaaS uncovers hidden business relationships using graph technology(similar to those used by LinkedIn, Facebook and Google), to reveal insights for competitive advantage. By going beyond just master data, and including transactions and interactions, a modern PaaS forms the foundation for analytics and machine learning. A new breed of PaaS allows IT teams to respond to business needs for process changes, or new sources of data in a timeframe previously deemed impossible.
#10. Business Cost Reduction & Controls
Many IT departments require business approval for funding of projects, so a focus on their own IT costs are mutually beneficial. However business teams also spend billions every year in their search for agility on disparate tools for business intelligence and self-service data prep. IT needs to deliver a reliable data foundation upon which business teams can gain the trusted and relevant insight they need, without searching for a needle in a haystack through ad-hoc queries. Another area that IT can help is the significant cost of training of users on how to use new applications and tools.
A modern data management PaaS that seamlessly delivers data-driven apps can reduce or eliminate business’ reliance or appetite for standalone self-service tools. By delivering the right information into the hands of the right users at the right time these next generation role and context sensitive apps are based on the exact same easy-to-use, zero training needs as popular apps such as Facebook, LinkedIn, Amazon and Google.
Thanks for reading this rather lengthy post. A modern PaaS is like a Swiss army knife, architected to handle any challenge past, present and future. I welcome your feedback and comments.
Digital Strategy is not a separate strategy, but instead a new lens on the overall business strategy that incorporates customer intelligence, sales & service optimization and digital marketing efforts (e.g. mobile, e-commerce and social). Key drivers of digital transformation among B2C organizations are profitability, customer satisfaction and increased speed to market. Whether you are a retailer, restaurant, travel company, media & entertainment company, lifestyle brand, or a consumer bank, you want to create a seamless, personalized and consistent customer experience across all channels (web, email, phone, stores) and departments (marketing, sales, support).
However, personalization is a double-edged sword. All digital transformation and personalization efforts would fail if data underneath is of poor quality, siloed and delayed. According to an estimate, poor customer experiences result in an estimated $83 billion loss by U.S. enterprises each year because of defections and abandoned purchases. On the contrary, if done correctly, it can considerably boost your business (Amazon’s conversion to sales of on-site recommendations could be as high as 60%). Some of the top of mind issues discussed during various sessions included:
Garbage in – garbage out.
Today, hyper-personalization is possible because of digital transformation enabled by cloud, mobile, big data, internet of things and many more cutting-edge technologies. Similarly, companies have invented great processes (order-to-cash, supply chain management, onboarding, provisioning) to manage customers, prospects, suppliers and partners. What’s still not treated as a top priority is the quality of data driving these processes.
The thought was echoed by other participants who discussed how reliable data is the key to effective customer experiences.
Data silos within the organization.
Being able to understand and monitor end-to-end consumer journey is vital. Yet, it is not uncommon for each team or function within an organization to define and measure customer experiences independently, in isolation. The result is disconnected global operations, fragmented multichannel visibility and incomplete views of customers that slow down all digital transformation efforts. Data-driven applications built on a Modern Data Management platform gives you not only the 360-degree view of your customers, products, channel partners, or suppliers but also a contextualized view of relationships among these entities. More importantly, it helps you create a single-source of truth across sales, marketing and support to provide the right customer with the right offering at the right time, thus enhancing the customer experience.
Data silos across organizations.
Co-innovation, co-creation and collaborative curation of consumer information, at a big data scale, can open the door to new possibilities. For example, personalized recommendations for food, movies, hotels and shopping can be packaged together for a particular consumer if the companies in these different industries are willing to share data with each other. Furthermore, such data exchange helps these non-competing business entities to monetize their precious consumer data assets. As digital touchpoints proliferation continues, a Modern Data Management solution will help companies to trade reliable data currency in a secure fashion.
Business outcomes don’t feed the underlying master data.
There are no mistakes, only lessons. It is critical to get smarter with each interaction. A Modern Data Management Platform coupled with Machine Learning enables contextual information and helps you answer high-impact business questions such as – Will my customer buy this product or not? Is this review written by a customer or a robot? Which category of products is most interesting to this customer? And so on. On top of that, a Modern Data Management solution captures all actual business outcomes and enriches the master data in a closed-loop, thus continuously fueling the recommendation engine for making smarter predictions.
It’s time for data to be managed in such a way to make true digital transformation happen. Once Modern Data Management is in place, a consumer brand can reap substantial benefits on a continual basis. Starting with proper data quality and alignment of key data assets across systems, departments and channels, it helps build a reliable data foundation for all your digital transformation initiatives. Businesses who will timely address this challenge will be ahead of the competition.
I attended a CMO Summit recently, networking with heads of marketing from a wide range of F500 companies from GE, Starbucks, Nike, Coca-Cola, NBC Universal and more.
One of the workshops -hosted by a senior marketing strategist from a well-known media and entertainment company- revealed some interesting feedback from an attendee survey. It resulted in a long list of wishes (beyond the traditional 3 allowed) that CMOs wanted granted. Therein lies the rub of the 5 I found most illuminating:
1. Wish for better data
No surprise here. They complained that their data is distributed across systems, and most don’t trust the quality of the data. As long as each group within an enterprise continues to operate on their own view of the customer, product or location, not only will information continue to be siloed and inconsistent, but critical relationships between entities and the 360 degree view will never be attainable.
2. Wish for better access
Marketing feels it’s so hard to get data they know exists in other departments; they’d rather pay an outside firm for the same data than rather than try. This is such a shame since it’s not cheap to buy data. Some interesting statistics quoted (from Gartner) stated that 99.5% of data is never analyzed. And companies spent $21 Billion buying and procuring data this year. Ironically this is less than 1/3 of the $65 Billion that is forecasted to be spent on SEO. Which goes to show that some marketers value being found, more than they want the data to understand what’s going on. Most did not understand that data acquisition could be simplified through Data as a Service.
3. Wish for better collaboration
Marketing and IT still aren’t on the same page when it comes to how to manage and use the data. There was significant discussion and debate about the gap between IT efforts and marketing needs. Topics mentioned included how the CMO was morphing into a hybrid CMO/CTO role, as well as the intermediary role of a CDO or Chief Innovation Officer, that bridged the gap between the two. How to get skilled marketers more tech savvy was also a topic. The facilitator had a question that stopped all the CMOs in the room in their tracks. He asked “Who thought of bringing their CIO counterpart to this event”. Crickets.
4. Wish for better insights
Personalized contextual customer experience is the goal, but most don’t know how to get there. There were several vendors offering mobile location technology, and the ability to track individual’s whereabouts and to deliver them in context offers and experiences. Ranging from auto check-in to hotel rooms, to free coffee coupons. Most in the room thought it was interesting, but clearly it would be a challenge getting just the foundation of core customer data in place before something like that would be on their radar. Further those in B2B marketing wanted personalized insight for better account-based marketing and sales execution.
5. Wish for recommendations
Many admired Amazon’s recommended products capability, and think it’s the tip of the iceberg. Recommended or suggested products provided by Amazon was lauded as an example of knowing the customer well, but most quickly agreed that even Amazon had a way to go to improve the targeting and the capabilities were in its infancy as closed feedback loops to track the outcomes of those recommendations were needed to improve recommendations and measure ROI.
It was eye opening to hear first hand how the top marketers from the largest organizations expressed their universal need for better data, access, collaboration, insights and recommendations. This represents an opportunity for IT to bridge the gap with new modern data management platforms to grant marketing’s 5 wishes, but other groups across the enterprise.
5 Things CIOs and CDOs Need to Know About Pokémon GO
Disclaimer: I was never part of the Pokémon craze back in the 1990s nor have I actually played Pokémon GO (the Guardian has a good Pokémon GO 101 guide here), however like many I’ve felt and seen the phenomenon both virtually in social media, and physically with people wandering around streets with their phones trying to capture them.
Because Pokémon GO involves a lot of SMAC (Social, Mobile, Analytics, Cloud), and tons of data – topics I’m constantly immersed in given my role as CPO at Reltio – I have a few observations to which may help CIOs and CDOs.
#5. Security risk via BYOD or casual access via personal devices
If you have a Bring Your Own Device (BYOD) policy, or employees occasionally accessing corporate data from their own devices, Pokémon GO increases the risk of security breach, data loss and intrusion.
One of the security or privacy holes that was uncovered involves permissions being granted to Google emails, docs and other areas by unsuspecting Pokémon players, when they used their iPhones and Google user accounts to authorize and play the game. While this issue has been addressed through an update by the game creator Niantic, to now collect only “basic” info like user ID and email address, anyone who previously downloaded the app will have to update it for it to take effect.
If you have employees who are outside the US or in geographies where Pokémon GO is not yet available, there are reports of “evil” APKs (Android Application Packages) that enable game play through “sideloading” which loads apps outside of the official app store. These apps could potentially spy on or gain access to data.
While the risks presented by Pokémon GO aren’t unusual as compared to any other popular application, its global phenomenon and ubiquity, coupled with increasing BYOD, and personal device access to corporate something that CIOs should be aware of. Not to mention theft of devices from thieves apparently laying in wait at locations.
#4. Data monetization could exceed in-app purchases in value
According to Sensor Tower, a company that tracks app usage, Pokémon GO had 10M+ downloads within the first week of launch and is now generating more revenue than any other iPhone app in the US. While Pokémon GO doesn’t charge a subscription fee, it offers in app purchases such as Poké Balls used in battle.
Oddly Nintendo, whose stock soared shortly after the release may benefit the least from these purchases. Estimates have it that out of the purchase price of 100 Pokéballs, Pokémon 30 would go to Apple, 30 to Niantic the company behind the game, 30 to Pokémon and 10 to Nintendo. Nintendo does own 32% of Pokémon company, and Google does have an investment in Niantic, having spun it out last year.
But the interesting thought which might make CDOs sit up and pay attention, is that the value in the game in the short term may come from the in-app purchases, the data being gathered (even after alleviating Google account identity concerns) may be significantly more valuable.
Geospatial data captured about a player’s location at a specific time has tremendous value for advertisers and can be analyzed to offer services. Similarly images captured from the augmented reality could be used to build up a library, similar to Google Street view, or other as yet untapped purposes. But much of this data may be unusable, unless it can be accurately correlated to other elements of a user’s 360-degree profile, and levels of privacy are respected and addressed.
Again this “latent” data captured during the course of mobile phone usage is already happening today, and Pokémon GO just serves to magnify the data collection at scale. Enterprise CDO’s tasked with thinking about how to monetize their own corporate data assets within their industry first need to ensure that their data is clean and reliable, with privacy, audit and licensing controls before attempting this at home.
#3. Gamefication drives activity with expected and unexpected results
It’s been written that Pokémon GO is the perfect storm of nostalgia (for millennials who grew up with Pokémon), competitive spirit, social interaction, and a desire in us all to just immerse ourselves in something fun. Intentionally or not, Pokémon GO has actually gotten people exercising, moving around and engaging with the outside world. Because of the varied locations, people have been walking more than they have in a long time, even jumping as directed to play the game. Others have used driving services like Uber in an attempt to move around their area in a safe manner, while the lazy (and resourceful) are using drones to do their Pokémon GO hunting. With every new craze, good and bad things can result. Gamers have reported being robbed, and even finding dead bodies when searching.
In a traditional business setting, something that can motivate, inspire and deliver excitement and gratification at a personal level would be refreshing. New data-driven applications provide the framework for social collaboration, and even gamefication (points or rewards) as individuals and teams can compete on tasks from improving data quality, to providing feedback and insight into the strength of hidden relationships between people, products, organizations and more. As CDOs look to rally everyone across the enterprise to help govern, manage, and enrich data as a valuable asset, such concepts can play a big motivational role.
#2. Cloud and elastic compute is critical to handle spikes in demand
Even with the well publicized and documented value of public cloud and cloud computing, many remain unconvinced by the inherent value of public cloud. There are business reasons why companies due to real or imagined security concerns, are not ready or willing to adopt public cloud such as AWS, but the benefits of elasticity in both compute and storage are hard to ignore.
Continuous uptime and handling scalability spikes are just a small fraction of the benefits. Those mired in on-premises software are stuck upgrading once a year or longer, while multi-tenant platform and applications continuously deliver zero impact upgrades 3 times a year or more, giving companies the highest level of competitive advantage.
#1. Simple, easy to use UX drives engagement
Pokémon GO’s success can also be attributed to a low learning curve. Like Facebook, LinkedIn and other mobile and intuitive applications, no training, or formal tutorials are required to play and participate.
Continuous feedback through alerts and notifications when characters appear or are nearby, keep the user engaged, and as a cousin of gamification, UIs that show Pokémons captured ensure gratification and encourages continued engagement.
Today’s business applications need to evolve into their data-driven consumer brethren that are mobile, easy to use, and responsive. Notably Pokémon GO launched on both, iOS and Android at the same time, this is also a prelude to the expectations of business users who expect access to their data, anytime, anywhere and from any device.
Increasingly “smart” data-driven applications that use the vast amount of data accumulated can also deliver Apple Siri or Amazon “Alexa” like recommendations, truly helping the business user beyond just capturing and returning back data as entered by users.
One parting thought around Pokémon GO is the obvious question of when augmented and virtual reality will enter the business realm. Pokémon GO overlays characters on the screen in the location and setting, which could just be a precursor to the introduction of business UI in industries where a high-degree of immersion can be beneficial.
It’s been well documented that the vote doesn’t mean that the UK is leaving the EU tomorrow. Some speculate it could take until 2020 before any action is taken. But companies across the globe do need to plan for that eventuality, and one key area is ensuring that they remain agile with their data management, and privacy protection strategies.
Accountability of businesses to demonstrate compliance including privacy impact assessments, key in healthcare data, in which the risks to an individual during the use of that data must be detailed
Data erasure aka “the right to be forgotten”, meaning removing any historical activities made by individuals captured as part of their digital activities
Profiling which relates to the need to obtain permission from individuals before any of their profile data is used to evaluate their behavior. Credit scores are an example of such profiling
Data breach notifications that dictate the minimum acceptable time periods upon which individuals or organizations must be notified when profiles containing their data is compromised
If the UK is no longer part of the EU, this may seemingly free UK companies from having to conform. However the GDPR is likely to be enacted in 2018, before the UK would leave in say 2020. And the UK and other companies doing business in the EU would still have to conform.
Additionally the GDPR actually determines data security and privacy policies for members of another group known as the European Economic Area (EEA). The analyst firm further points out
Amazon Web Services and Microsoft are in the process of adding to their cloud facilities in the UK. IBM has already done so. All were trying to establish cloud centers close to what has become the emerging financial center of the EU.
While an article in the Financial times takes another perspective suggesting that
As we’ve seen by global reaction, and the gyrations in the stock market, the uncertainty is overwhelming.
Organizations who naturally see data as an asset for digital transformation, improved customer experience, and personalized targeting, have multiple hurdles to go through to conform to not just new regulations like GDPR, or even the EU-US privacy shield. The key for any organization wanting to do business globally is to use data management platforms and technologies that are agile enough to comply with all of these laws today, and as they evolve. Only then can they maintain their competitive advantage using data, and prevent their data turning into a compliance liability.
So maybe Brexit is just another wake up call for your company’s data management strategy.
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