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5 Data-Driven Business Trends For 2016

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In a recent global survey of nearly 3,000 marketers by GDMA / Winterberry Group, 81% described data as important to their marketing efforts. Data is becoming an essential ingredient in business success across all functional areas—not just marketing—as companies seek to turn insights into enhanced performance, greater productivity, better customer service, etc. No matter where you are on your data-driven journey, you’ll want to be aware of the following five data-driven trends in 2016.

1. Surge in Sensors

Gartner forecasts there will be 6.4 billion internet-connected things in 2016, up 30% from 2015. Sensors can be used to measure all kinds of things such as motion, light, temperature, humidity, air pressure, distance, and so on. In 2016, as sensors become smaller and cheaper, they will provide even richer levels of insight as they are applied to new settings and situations. For example, food and medicine manufacturers are looking at using temperature sensors to be alerted when products fall outside of an acceptable range to prevent spoilage. If you thought the recent data explosion has been overwhelming, you haven’t seen anything yet as the Internet of Things (IoT) continues to expand. Companies will not only need to worry about data collection from sensors, but also how they’re going to analyze the data for meaningful insights and apply the data in real-time within their business.

2. Advance of the Algorithms

For years, Amazon has been making product recommendations based on our onsite behaviors and purchase patterns. Statistical or machine-learning algorithms are behind much of the digital personalization we experience today. In 2016, we’re going to see algorithmic / programmatic approaches expand into unforeseen areas and become even more common. For example, during this year’s holiday shopping season, leading retailers such as Amazon and Walmart were relying heavily on algorithmic pricing. Both retailers repriced 15% of 18,000 product SKUs being tracked by 360pi (a pricing intelligence solution) on November 14th alone. Imagine the impact dynamic pricing will have on retail when it eventually expands into physical stores as well.

In addition, marketing will be significantly influenced by algorithms as more marketers adopt algorithmic attribution over traditional rules-based attribution models such as last-click. This new approach will remove much of the subjectivity that has plagued rules-based attribution models. In content marketing, we’re also beginning to see algorithms used to assemble and create meaningful content. In recent studies by Karstad University, people were unable to distinguish between what was written by sports journalists and machines. While these “robo-writers” may not entirely replace their human counterparts, they may begin to fill various gaps in content marketing strategies.

3. Trigger Transformations

Increasingly, business owners and marketers are relying on automation for handling more routine business and marketing processes, especially when it comes to event-based triggers. We’ve seen how a programmatic approach has been effective for email marketing (remarketing) and media buying (real-time bidding). In 2016, we’ll see data-driven triggers expand more in the area of mobile marketing.

In the mobile world, companies have new opportunities to engage customers based on their specific location such as sensing when an individual enters a store and triggering a personalized message or offer. It also provides businesses the ability to respond directly to their customers in the moment when a key event occurs. For example, if my Delta Airlines flight is delayed, I’m immediately notified by the airline on my smartphone and prompted to book an alternative flight in the Delta mobile app. Data-driven triggers may represent a great way to engage your customers in a more timely, relevant fashion--transforming your overall relationship with them.

4. Cross-Device Chasm

As consumers continue to expand their usage of devices (smartphones, tablets, desktops, smart TVs, game consoles, etc.), brands are struggling to identify and target people across multiple screens. In a 2015 survey, only 6% of marketers worldwide reported they had an adequate single view of customers or prospects across all devices and touchpoints. Unless you’re a behemoth like Facebook , Amazon, or Google with a large footprint of unique identifiers for people across devices, there’s not an easy way to unify customer behaviors across multiple screens.

In 2016, companies will increasingly focus on a combination of deterministic and probabilistic methods to overcome this challenge. From a deterministic perspective, more companies will require customers to log in or authenticate across their different devices. From a probabilistic approach, many companies will consider data management platforms (DMPs) and other means of algorithmic cross-device matching. Bridging the cross-device chasm will be a key priority in 2016 even though the initial forays may be incomplete or imperfect.

5. Data Democratization

As businesses become progressively data-driven, it becomes important to empower employees with data. In the past few years, significant advancements have been made in the areas of data visualization tools (D3.js, RAW) and data discovery (Tableau, Qlik). While these tools have fueled a self-service renaissance in the business intelligence industry, there’s still room for further improvements. The most recent wave of enhancements has made it easier for analysts to explore and share data, but in 2016 we’ll see further advancements to democratize the data throughout organizations so data becomes significantly more pliable for non-analysts. In many cases, this will mean an analyst-curated experience where business users can freely interact with a limited set of relevant metrics and dimensions, which goes beyond just consuming a static dashboard.

For the past few years, becoming more data-driven has been a key focus for many businesses. In 2016, we’re going to yet again see another increase in the volume, velocity, and variety of data. However, we’re also going to see technology assist us in more ways to address the inherent challenges and help us to harness its potential value. As data plays an increasingly prominent role in business, I can’t wait to see what new data-centric innovations 2016 will yield.

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