2020 Predictions Based on Current Quantifiable Trends

“Data and analytics leaders should actively monitor, experiment with, or deploy emerging technologies. Don’t just react to trends as they mature. Engage with other leaders about business priorities and where data and analytics can build competitive advantage.”
- Rita Sallam, Vice President Analyst, Gartner

It’s no secret that technologies like machine learning, AI, and predictive analytics have revolutionized how organizations are developing. But within these broad categories, several more specific data trends are particularly relevant. Organizations that pay attention to these now will thank themselves later when they’re able to keep pace with the next set of emerging trends in years to come. Here are the most disruptive data analytics trends of 2020 that will continue to mature over the next five years.

Augmented Analytics

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Augmented analytics (AA) allows for optimized decision-making beyond what many professionals are accustomed to. AA uses machine learning, AI algorithms, and a process called natural-language generation, which transforms structured data into our normal, natural language. Rather than pulling up the most relevant insights manually, organizations can automate this process and save loads of time. These insights can be made available to all important players, and the process saves them from having to be (or rely on) data scientists and analysts. AA has a lot of potential to be disruptive because it addresses the collective Achilles heel – that there are not enough data scientists and expertise to manage all the data that organizations are accumulating.

Data Fabric

Data fabric is a platform that allows for the convergence and management of data from different sources. Through this framework, data can be transported, combined, designed, managed, and protected across channels. For organizations that don’t want to convert or migrate data, data fabric offers a solution that doesn’t waste as much time. Closely tied to managing augmented data, data fabric allows organizations to support data at scale from diverse silos like cloud, SQL, and more. In the past, organizations aimed to have all their data stored in one warehouse. Today, we’re moving beyond this to a more comprehensive goal.

Explainable AI

Explainable AI will be essential for organizations to successfully manage the rise of AI in business. With such complicated models being employed more every day, it’s critical for organizations to learn how to understand and explain their results for internal monitoring. Detecting for bias and privacy issues, and ensuring regulations are observed, is of growing importance and difficulty.

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Explainable AI is critical because it addresses the growing “black box” problem in which data experts do not know exactly how and why an AI tool came up with the answer it did. Many AI algorithms can’t be examined after they generate insights, leaving organizations to wonder about the accuracy of the information. With explainable AI, the models and steps involved can be more carefully scrutinized. This way, organizations can repeat these processes and have them be transparent rather than hidden.

Continuous Intelligence

Continuous Intelligence is as useful as it sounds, providing the ongoing capacity to make real-time business decisions based on analytics. Organizations with situation-specific data can make informed decisions or receive predictions on what to do next. Central to this process is a focus on outcomes and automation. This may sound like what many organizations are already doing, but it goes a step beyond that. You can analyze data as it is created, visualize aspects of your organization, make predictions faster, learn from unstructured data, and automate actions immediately. In today’s world of developing technology and ongoing change, continuous intelligence is a no brainer for the future of business.

Mobile Intelligence

Perhaps the least surprising trend, the mobile intelligence (MI) framework will be built upon to achieve better results. Mobile app development will be geared toward a better work experience, stronger internal communications, and stronger B2C communications. With consumers using mobile devices for more and more tasks each year, it’s clear that mobile is being embraced on all levels. This means organizations need to have MI at the front and center of their strategy. Much like continuous intelligence, MI allows for real-time insights that help organizations act more quickly.

Data Diversity

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In 2020, we’ll see an even stronger focus on bridging the gap between diverse data sets as organizations grapple with what tools to use and how to combine data in the most efficient way. When data sets become too large, sometimes the simplest solution is to break it up into smaller, more meaningful sets. The key to truly diverse data is to look beyond what’s obvious, not just focusing on the data that would be easiest to collect.

“Non-representative data sets are less likely to yield workable insights than those which cover all facets of the issue under investigation. It’s also true in terms of the variety of data available. With the sheer divergence of datasets available, it’s more critical than ever, as insight can often be found in unexpected places. Thanks to breakthroughs in technology such as image analysis and natural language processing, meaning can be extracted, in an automated way, from video, handwriting, recorded speech and the text of emails and social media posts.” - source

Organizations that dig in and engage with these trends now will be much better prepared for data advancements in the years to come. Meanwhile, those that don’t may have a lot of extra headaches later on.

Being data-driven is no longer a luxury reserved for the biggest and wealthiest organizations. It’s an accessible reality for all. Moving forward, focus will shift toward refining data management processes and accessing deeper layers of expertise for sharper results – better customer service, higher marketing ROI, and more confident decision-making. That’s how data-driven organizations will move onward and upward in 2020.


Data Orchestration is the New Data Automation

The advent of the big data age had companies scrambling to not only collect more data but automate processes to help manage the workload. Businesses were learning in real-time – through trial and error – how to collect, store, clean, and analyze heaps of information.

More than a decade later, tech advancements haven’t slowed down. There are more tools to use, more skills to learn, and, according to scientists, about 295 billion gigabytes of data in the world. How do businesses extract precise insights that can guide their marketing strategy and boost ROI? In other words, how do we put all this data to good use – and prove it?

Needless to say, this process was challenging enough, and many marketers, organizations, and data scientists are still wondering whether their efforts to utilize data are making a real impact.

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But as the dust settles, many businesses have landed on their feet, wiser and better equipped to thrive. Now that we’ve gotten a handle on data automation 101, we’re beginning to see an even greater level of advancement on the horizon – and that’s data orchestration.

What Is Data Orchestration?

In a nutshell, orchestrating data works just like orchestrating a symphony – all instruments must be in tune, in rhythm, and working in unison with all other parts. When this falls into place, being a data-driven business is much easier. But when data processes are not in harmony, it can lead to all sorts of kinks throughout your data pipeline.

From preparing data to analyzing, drawing conclusions, and taking action, your data may travel through various applications and departments. So what happens when the right synthesis doesn’t take place?

Disorganized Data (The Problem)

One of the biggest issues that can arise from a lack of data orchestration is unusable data. Whether it’s poor quality, inaccurate, or not in the correct format to use, this is the dreaded ‘dirty data’ problem that thwarts many companies. The impacts of disorganized data are surprisingly weighty. According to an Experian report, companies from around the world feel that an average of 26% of their data is dirty.

 

Another problem arises when data history can’t be tracked.

The provenance of data products generated by complex transformations, such as data orchestration workflows, can be extremely valuable to digital businesses. From it, one can determine the quality of the data based on its source, provide attribution of data sources, and track back sources of errors and iterations. Data provenance is also essential to organizations that need to drill down to the source of data in a data warehouse, track the creation of intellectual property and provide an audit trail for regulatory purposes.” - Chris Scalgione

Part of eliminating data silos is eliminating disparate tools that are difficult to use in tandem. Ideally, teams will have access to the same data and know how to use the same platforms to manage it holistically.

Cohesive Data Management (The Solution)

So what can a business do if it’s wading through the swamps of a data disaster? Data orchestration means carefully mastering each interaction with data from start to finish.

Let’s start at the beginning with data collection. Customers are interacting with your brand at many touchpoints – advertisements, websites, social channels, and, perhaps, in person. Each of these data sources can provide a wealth of insight – if you’re equipped to collect it in real-time.

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Next, data integration. Coming from various sources and in various formats, your data needs to be merged in one place. Once data is profiled, you can decide how it needs to change to create one uniform data set. This step is integral for accurate interpretation later on.

From here, data-enrichment processes can increase the quality of data, readying it for analysis and, eventually, decision-making. Enrichment allows for a better understanding of customers and what they respond to over time.

The tools and platforms you choose play a pivotal role in ensuring each of these processes is carried out efficiently. Currently, many data platforms have one or two strengths they specialize in, but can’t orchestrate the whole process. For this reason, many organizations must manually examine their data pipeline to find weak spots and refine the procedures.

The Future Is Orchestrated

In the end, automation is only as valuable as the tools you use to carry it out. High data quality and careful coordination must come first. The places we mine data and the uses we find for it are multiplying, along with data privacy regulations. Thus, it’s more important than ever to have a sophisticated data management system that leaves nothing to chance.

In the next ten years, more businesses will begin their trek toward a data-driven future. It’s through this transformation that companies leading the pack will be able to scale comfortably and make truly data-informed decisions.


ONE12th.io - Data, Marketing & Automation

Driven by Data or Lost in the Details?

5 Questions that Matter in Marketing

From the advent of the data age, businesses have struggled to harness new technology to make data-driven marketing decisions. From lead conversion to better ROI, and now customer engagement, marketers are eager to make use of the power data has endowed them with.

Every modern company aspires to be ‘data-driven.’ The problem is, achieving this coveted label isn’t so simple. With new power comes new complications – keeping data clean, separating facts from assumptions, tracking the right metrics, and choosing appropriate platforms and tools, just to name a few.

So how can businesses know if they’re truly data-driven or getting stuck in the various pitfalls of wielding unfamiliar technology? While the details vary for each business, a few simple questions can provide clarity.

1) Is a cross-channel strategy employed and is it getting results?

Most businesses know they need to reach out to their audience through multiple online channels. The easy part is creating accounts and having a presence on all of these relevant channels. The hard part is creating cohesion between them. A cross-channel strategy accomplishes two valuable objectives: It ushers customers smoothly from one step of the marketing funnel to the next, and it amplifies the impact and message of the overall marketing strategy.

A cross-channel strategy that is employed correctly will strengthen brand recognition and help customers remember specifically what it has to offer. A business without a cross- channel strategy ends up with choppier communications and a value proposition that lacks unity.

2) Is data being collected and analyzed in silos?

What happens when the findings of one dataset contradict another? How can marketers avoid comparing apples to oranges or drawing conclusions based on data that is too limited and specific? Ultimately, collecting and analyzing data on several separate platforms increases confusion and makes it harder to create a cross-channel strategy that makes sense. Platforms that allow for a centralized data hub give a broader perspective of the health of a business’ marketing efforts. These platforms also increase communication and collaboration between team members who should all be accessing the same data reports.

Fortunately, data silos are a problem that businesses are making great strides in solving –

According to a recent study by Teradata, “43 percent of respondents said they have achieved fully integrated data across teams, compared with just 18 percent in 2013.”

3) Is data being analyzed and action being taken?

It sounds all too obvious, but even highly developed marketing teams can get caught up in the chase – that is, collecting data endlessly as if collection is the goal itself. In addition, companies can easily lapse into using data strictly in hindsight, looking back at past results to understand what already happened. This neglects the bigger purpose of data, which is to forecast, improve future outcomes, and prevent problems. It’s crucial for businesses to stay focused on answering the right questions with data rather than endlessly collecting larger and larger pools of data. Bigger is not always better – especially if the ‘why’ behind the project grows hazier as the data size increases. If data is collected and analyzed successfully, but no clear information can be learned from it, it’s a red flag that marketers need to go back to the drawing board. Even the most skilled data analysts with precise conclusions won’t make an impact if decision-makers don’t head their advice.

4) Is testing central to how the organization operates?

At the heart of every data-driven organization is testing. Whether its split testing two versions of an ad campaign, swapping email subject lines, or anything else, a data-driven company tests whatever has an unknown outcome. A large corporation with several product lines might run dozens of marketing tests per day to pinpoint optimal ways to reach customers.
This testing culture is born from the realization that there is always another way to tweak, streamline, and optimize processes for best results. Thus data-driven organizations embrace testing as a means of continually growing their reach, understanding customers more intimately, and increasing revenue. As predictions are made about inventory, sales, or marketing, companies can later look back to assess the accuracy of these predictions and make changes to improve.

5) Where is most of the time spent?

A good rule of thumb is that marketers should be spending less time on data collection and reporting, and more time using those insights to create change. According to Hubspot, wasted time can be reduced by making small changes, such as automatically updating reports daily. Simplifying the data collection and reporting process makes space for data analysts to spend more time on what matters - generating thoughtful insights and using the information to solve problems. Companies must have sufficient time to reflect on the bigger picture underneath their data - What is the deeper meaning and why are these patterns playing out?

Ultimately, a business is only data-driven if it takes consistent action based on definitive findings. For that to happen, a business needs to have sound data collection and analytical capabilities. In addition, being able to segment datasets without going too far as to create silos is critical.

This delicate dance of using data intelligently isn’t easy, but for the persistent marketer, it pays off in spades. A data-driven company is a company that knows the health of its customer-base, where its revenue is coming from, and what marketing decisions to make next. Businesses no longer need to leave these immensely important choices to chance. With data, there can be certainty, and with certainty, peace of mind.


What Industries Will Incorporate VR in 2019?

We've officially reached "the future" people have been talking about for decades - an age where virtual reality (VR) can impact actual reality. Contrary to popular belief, VR isn't just for avid gamers or scientists who love to marvel at new technology. In fact, it's already on its way to radically transforming various industries. One study estimates that the global virtual reality industry will generate $21.5 billion - a 4x revenue increase in just four years. In 2019, we'll see even greater efforts to weave VR through day-to-day life.

Retail

With the continuous growth of e-commerce businesses, many brick and mortar retailers are in crisis. These stores are now faced with unique challenges from suddenly having to compete with online giants like Amazon at every turn. But all is not lost - There are plenty of ways both brick and mortar and online retailers can benefit from VR. Clothing stores are considering how shoppers can virtually experience outfits without even having to try them on. Soon, shoppers may not even have to leave their bedroom to access a virtual mall of products with which they can interact. And while many experts are skeptical of just how readily consumers will latch onto retail-related VR experiences, a survey by J. Walter Thompson Intelligence revealed that 80% of Generation Z respondents were more likely to visit a store that offered VR. Brands like Topshop and North Face have already implemented VR into the buying experience with stunning results.

Training

Several industries will incorporate VR for training purposes, saving on resources and providing a more thorough learning experience for new employees. Law enforcement, healthcare workers, firefighters, military personnel, and even astronauts can be prepped for dangerous scenarios they would otherwise have no way to prepare for. Rather than reading from a textbook, people in these precarious careers can gain real practice engaging with difficult stimuli right away. While still in the early phases of implementation, VR training has the potential to save lives and help professionals avert disasters in real life. Even in lower risk careers, VR can assist employees in learning necessary skills like customer service and hospitality management.

Marketing

It's no surprise VR has the potential to revolutionize how marketers promote and sell products. What better way to convince than to give consumers a positive and memorable experience with a product? This may be marketers' response to millennials' denouncement of "stuff," as research repeatedly shows they value novel experiences over things. This style of marketing goes above and beyond to generate hype, offering a taste of a satisfying product or service. Omnivert is a platform that offers brand VR advertising experiences that consumers can explore from their iPhones and computers.

Manufacturing

Imagine a world where products can be made without risk. VR is giving new hope to manufacturers that need safe, efficient, and affordable ways to create prototypes. For these businesses, "VR as a service" is becoming a hot topic as well. Over the next several years, manufacturers may find that investing in this type of service is a small price to pay for a super-reliable design and prototype tool.

In the past, virtual reality was an out-of-reach luxury for most businesses. But Forbes indicates that nearly "7.5% of the world's valuable brands" are already employing industry-specific VR. Furthermore, accessibility has increased with more than 250 unique VR headset options now available on Amazon.com. While we won't know the full impact of VR in business for years to come, it's clear that it has already made an indelible mark on the world as we know it.


How Watson Is Changing Marketing

Most people have heard of IBM's Watson artificial intelligence software. Watson has come a long way since winning Jeopardy and is being used for a variety of applications. Brands and marketers face more competition than ever before and are awash with data they are only just beginning to use. Watson can parse through that data and provide actionable insight to help brands make lasting connections with consumers.

1. More Targeted Promotions

The holy grail of advertising is being able to sell the right product to the right consumer at the right time. Traditionally, advertisers paid for spots during television shows or sporting matches to reach a particular portion of the larger viewing audience. Over time, advertisers have been able to drill down to more granular target audiences and tailor their messaging accordingly. IBM Watson takes targeted advertising a quantum leap forward. Watson can target even more specific subgroups and offer dynamic advertising based on a variety of factors. For example, IBM is partnering with personalized data marketer Jivox to craft real-time contextual ads. If the weather turns cold, customers can be presented with ads or coupons for nearby coffee chains; ads can even include animated snowflakes if it begins to snow outside. Weather is just one of many data points that can be used to power data-driven digital marketing campaigns that boost sales.

2. Live Testing Advertisements

Another area where IBM Watson can support marketers is analyzing reactions to live testing advertisements. Normally, marketers and brands test early versions of advertisements in a simulated environment and then make adjustments based on feedback. This could be focus groups or other small test environments with a small number of subjects. Live testing involves analyzing reactions to marketing messages in real time and make adjustments automatically. For example, a car brand wants to develop a marketing campaign for a specific vehicle. The brand might make dozens of versions of the advertisement highlighting specific aspects or selling points. IBM Watson can test combinations on Facebook or other platforms and zero in on the most successful combination, creating an ad that is more likely to sell cars.

3. Predictive Analytics

Collecting data doesn't mean anything without the tools to parse through that data and find relationships in the numbers. Watson's Predictive Analytics tools help marketers identify those relationships and develop actionable insights. For example, a fast food chain wants to determine the attractiveness of offering a 20% off coupon during the fall. Watson can parse through spending data from previous quarters to determine which customers are most likely to respond to a coupon. That analysis can be based on previous behavior with coupons, income levels, and the length of the customer relationship. Watson can even determine when during the fall such a coupon would be most effective. This allows companies to maximize their marketing budgets and get the most bang for their buck. Predictive Analytics is also iterative; the longer the relationship with a customer, the more accurate and effective a promotion becomes.

Marketing is increasingly becoming data-driven and marketers need the tools to parse through data and make actionable insights. Watson gives companies the ability to better understand their customers by finding those quantitative relationships. Whether it's trying to understand which customers to target or what marketing messages will best resonate, Watson is changing the face of modern marketing.

 


New Orleans: On A Collision Course with the Tech Industry

Starting May 1st, over 20,000 attendees, including over 3,000 CEOs, will descend upon New Orleans for the Collision Conference, "America's fastest growing tech conference."

 

 

The event will be taking place at the exact same time as the famous Jazz Fest. Considering this is Collision's second consecutive year in New Orleans, it's safe to say their time last year had a large effect on where they'd be holding the event this year.

 

But there could also be other intentions involved. There are currently two prominent tech hotbeds that we know of in America: San Francisco and Austin. San Francisco is falling out of favor because of it's exceedingly high cost of living rates. Austin is reaping the benefits, boasting a corporate tax rate of zero, relatively affordable rent, and bohemian qualities of its own.

 

These hubs are on the West Coast and in the heart of Texas. Could it be time for the East to have a tech center of its own?

 

That may be determined by just how influential Collision 2017 is. The event's coordinators even discuss how they're "looking to feed off of the energetic, positive-vibe atmosphere created in New Orleans. [The city] has been looking to establish itself as a hotbed for tech, and having Collision there this year supports that effort."

 

Four types of people will be attending:

 

  1. Tech startups looking to pitch their idea and find funding to grow it
  2. Entrepreneurs and venture capitalists looking for the next great thing to invest in
  3. Wanna-be startups that aren't quite at the pitch stage yet, but looking to explore technology to come up with their future business.
  4. Our very own performance ninja, Emira!

 

To summarize, there are going to be startups. There are going to be investors looking to invest in a startup. And there are going to be potential startups watching what type of startups are being invested in.

 

Those in the third tier should guide their interest to the IMPACT startups. With the current U.S. administration not too keen on the idea of environmental preservation, startups promoting sustainability could be a huge hit, in terms of private investment, for the future:

 

"11 of the world's most impactful startups are coming to Collision. These startups were selected from more than 200 entries to exhibit as an IMPACT startup in collaboration with Accenture Strategy. They were selected on five criteria including: product maturity, growth potential and ability to execute."

 

Collision's ALPHA program is also a channel for the promotion of specific startups with potential, as are the designated 'Mentor Hours', 'Office Hours', 'Roundtables', and 'Workshops'.

As far as entertainment goes at the event, the PITCH event looks like the go-to:

 

"PITCH is the startup competition at Collision that brings together the world's leading early-stage startups for a live on-stage battle.

 

The top 66 startups that apply will get to present in front of distinguished investor panels, influential media, and global partners. Startups will battle it out across three days for a chance to present in front of thousands of attendees on Center Stage and be crowned winner of PITCH at Collision 2017."

 

 

Now as far as entertainment goes, in terms of New Orleans, well, there's everywhere else. Among the 13 standalone conferences that are a part of Collision include 'Culture Summit', 'Sunset Summit', 'Pub Summit', and 'Night Summit', which are all further opportunities for startups to meet and mingle with fellow startups and even CEOs who venture into New Orleans' famous nightlife.

 

Remember: this will also be coinciding with Jazz Fest. There's a bar on every corner and literally every weekday is a party. Who's to say that a lucky startup won't end up receiving a $100 million investment at 4AM over Po Boys?

 

 

Every industry under the sun will be representing and pitching their ideas, while workshops will be held for code, content, data, design, e-commerce, enterprise, fintech, IoT, marketing, music, security, social media, and sports.

 

Aside from the four aforementioned conferences that will be taking place once the day ends, there will also be nine conferences with potentially less time with libations:

 

AutoTech: Leading gathering for autonomous vehicles, connected cars, drones and the internet of things.

binate.Io: World’s leading data conference, connecting data scientists, analysts, hackers, and engineers.

Creatiff: Leading design conference, connecting designers and creative.

FullSTK: Leading conference for developers, investors, futurists, engineers and computing experts.

MusicNotes: Leading music & tech conference where global brands, artists,   labels, marketers, investors and icons meet.

Panda Conf: For 5,000 marketers & technoligists where industry giants, global CMOs, leading brands, investors, agencies and adtech startups meet.

Planet Tech: Brings together startups, giants, influencers and voices from     fields of sustainability, green & environmental tech, energy efficiency and clean tech.

SaaS Monster: Connecting more than 5,000 CIOs and CTOs, buyers and sellers, experts and investors, startups and established companies.

Startup University: CEOs, founders, industry leaders and investors on what’s going to make your startup a success.

TalkRobot: For AI, robotics and hardware experts, connecting thousands of leading companies, startups, investors, engineers, roboticists and researchers.

 

And what's a conference without its speakers, right? I bet when you clicked on this article you didn't expect me to announce that Jessica Alba (Founder of The Honest Company), Terrell Owens (NFL player turned philanthropist and entrepreneur), Ja Rule (Fyre), and Wyclef Jean (Musician and philanthropist) would all be speaking.

 

For those more interested in the technical side of things from prominent figures in their industry, though, we've compiled a short list of people with clout you may be interested in:

 

Neal Mohan – CPO YouTube

Alan Schaff – Founder Imgur

Alexis Ohanian – Co-Founder Reddit

Kevin Lin – Co-Founder and COO Twitch

Suzy Deering – CMO eBAY

Stan Chudnovsky – Head of Product for Messenger – Facebook

Jamie Moldafsky – CMO Wells Fargo

Karen Walker – CMO Cisco

Jason Robins – Co-Founder and CEO DraftKings

Nigel Eccles – Co-Founder FanDuel

 

295 speakers overall will be present, including an astronaut, journalists, the Deputy Assistant Attorney General of the United States, and the former governor of Colorado.

 

This year's event could very well signify yet another tech migration and we're going to be a part of it. Stay tuned for our follow-up blog when we get insider information from our source within the event!