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July 12, 2017

Creating a Connected Data Ecosystem

The number of marketing technology tools is rising at a staggering rate, having nearly doubled YOY in 2016. On average, 51% of organizations use 21 or more digital marketing solutions. While having the ability to access all this new information provides unprecedented insight, it frequently results in an overload of data siloed in disparate systems. Marketers are buried under a landslide of fragmented campaign metrics, products, customers, purchases, and more. And there’s seemingly no end in sight; Gartner reports that 50-65% of marketing executives plan to spend more on marketing technology in the coming year.

To make meaningful use of all this data, metrics need to be reviewed cohesively. Without a full holistic view, it’s impossible to get a complete understanding of the real story. Only analyze existing customer behavior and you may miss out on opportunities to attract new audiences. Only review site traffic from media placements, and you lack an understanding of why your customers are loyal to your brand, or how to create more of them.

The problem is that most marketing teams don’t operate with systems that talk to each other. They end up trying to manually analyze disparate data points to uncover insights, a practice that is neither scalable nor responsive in real-time. This data fragmentation is costing marketers real dollars as they lose the ability to effectively optimize campaigns and fold learnings into future plans.

An example of how some marketing departments utilize data today:

The solution begins with creating a connected data ecosystem. The concept is simple—collect all data points into a centralized system able to analyze them en masse and surface actionable insights in real-time. Using those insights, marketers can then start to roll out personalized content, translate strategies across all channels, and efficiently improve customers’ experiences.  While the initial creation of the connected data ecosystem can be time-consuming, it pays off. One example: Annuitas Group reports that businesses that use marketing automation to nurture prospects report a 451% increase in qualified leads.

 

Based on our experience with building ecosystems for clients, we have created a four-step process that we follow:

  • Discovery: we assess all the various systems that are collecting data around your organization. We also identify areas where the data returned may be less than perfect in quality–a very common occurrence. During this period we also outline the shared objectives and definitions of success across all the stakeholders.
  • Solution design: using our learnings from the Discovery period, we design a customized solution that aligns to your business objectives. We build a roadmap using multiple analytic approaches across our four service categories: Performance analytics, marketing sciences, research, and business intelligence.
  • Analyze: This is where the magic happens. Now that we’ve designed your ideal system, we begin to collect the data and review the outputs using our team of data analysts, statisticians, and social scientists to uncover those insights that will truly give your business the competitive edge.
  • Insights: This is when our team works with marketers and other members of your organization to communicate our findings and share recommended actions to meet your KPIs. Once the initial foundation is built, this process can be repeated multiple times over the course of the year, ensuring your teams are always up to date on the latest findings and fully able to use fresh data to inform future plans.

The creation of a connected data ecosystem takes some effort but pays off almost immediately by making teams run more efficiently with a full understanding of the current state of their business and what levers they have to achieve their goals.

January 19, 2017

Intel To Invest $100m In Retail Tech Anchored By IoT, Data-Led Platform

why-intel.jpgIntel is planning to invest over $100 million in the retail industry over the next five years and at the heart of that is the Intel Responsive Retail Platform (RRP), an IoT solution that will take retail to the next era of highly efficient and personalized shopping. Through RFID, video, radio and other sensors, it will enable easy, holistic integration, help to deliver a 360-degree viewpoint of retail from the store floor through the supply chain, and deliver real-time, actionable insights.

 

The haves (data) and the have not.

January 11, 2017

Medicaid’s Data Gets an Internet-Era Makeover

10NUNA1-master768-1.jpgSan Francisco start-up Nuna has built a cloud-computing database of the nation’s 74 million Medicaid patients and their treatment. Health data on its own — billing, diagnostic and treatment information, typically recorded in arcane, shorthand codes — is not very useful. But if it can be aggregated and analyzed economically and quickly, that data is seen as a vital ingredient in transforming health care.

Data, analytics and the system-wide view

November 30, 2016

Spotify Crunches User Data in Fun Ways for This New Global Outdoor Ad Campaign

spotify-ooh-ep-2016.jpgSpotify puts its vast trove of listener data to playful use in a new global out-of-home ad campaign—its largest OOH effort to date—with executions that playfully highlight some of the more bizarre user habits it noticed throughout 2016. The work began rolling out Monday.

It's been weird.

November 9, 2016

We’ve Got Human Intelligence All Wrong

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The human brain has nearly 100,000 times as many neurons as the bee brain, yet the rudiments of many of our most valued behaviours can be seen in the teeming activity of the hive. So what’s the point of all that grey matter we hold in our skulls? And how does it set us apart from other animals?

Does size matter?

October 26, 2016

Being Human in the Age of AI, Robotics & Big Data

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According to a recently published report by Forrester, six percent all US jobs will be replaced by automation over the next five years. Ten years from now, 16% of all jobs will be automated. Described as “a disruptive tidal wave,” the transformation will mostly impact transportation, logistics and customer service sectors. 

The bots are coming.

October 19, 2016

Meet the Woman Who Could Turn Jet.com Into the Digital Era's Ultimate Challenger Brand

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For the past year and a half, Liza Landsman has taken on a massive challenge: overseeing marketing, branding and analytics as chief customer officer of ecommerce startup Jet.com as it attempts to compete with the retail Goliath that is Amazon. Landsman is building the Jet brand around the promise of making shopping fun through a gamified process that aims to shake up the way people shop for everything online: from household products to books, music, appliances, electronics and groceries.

We love a challenge.

October 18, 2016

How Airbnb Uses Data Science to Improve Their Product and Marketing

checkin-gaps.jpgHaving grown quickly from a niche site providing accommodations for high profile events, Airbnb turned the hospitality and travel industry on its head and generated a great deal of press and brand recognition in the process. Since its humble beginnings, Airbnb has made no secret of its heavy use of data science to build new product offerings, improve its service and capitalize on new marketing initiatives. Here’s how they do it – and what you can learn from them. 

I dream of data.

October 17, 2016

‘It’s PR’: Fashion Marketing is Failing to Understand Data

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Luxury fashion houses are notoriously slow-movers when it comes to embracing digital technology. Industry reports show that online is the fastest growing channel for luxury goods by far. According to Bain research, while the entire luxury goods market is expected to grow by 2 to 3 percent in the next five years, the online luxury goods market is expected to grow by 20 percent in the same period. With the entire industry behind in moving to online shopping, that mindset has affected is data-driven marketing growth as well.

That's a chic number.

September 27, 2016

A Netflix Exec Explains the Simple But Painful Process That Allows the Company to Thrive

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The biggest mistake most companies make when choosing a strategy is "listening to the Hippo — the Highest-Paid Person in the Organization," Neil Hunt, chief product officer of Netflix. At Netflix, data rules the company. Really committing to this idea means loads of A/B testing and a willingness to accept a high rate of failure.

Data and vision equals transformation.

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