Here’s how to get the most out of your marketing analytics investment

Build organizational structure and develop analytics leaders who bridge data science with marketing strategy to improve your return on investment.

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Gartner recently published their Predicts 2019 research report, outlining several converging trends that pose a threat to CMOs and marketing organizations. The report also makes several bold predictions including that “by 2023, 60 percent of CMOs will slash the size of their marketing analytics departments by 50 percent because of a failure to realize promised improvements.”

The number one success factor for CMOs today is the ability to effectively leverage customer data and analytics. And yet, according to Gartner’s report, companies today are clearly not demonstrating consistent return on that investment, a problem which often stems from a lack of marketing analytics leaders and the organizational structure necessary to effectively translate data and insights into action.

To discuss in more detail, we chatted with one of the authors of the Gartner report, Charles Golvin, to explore what CMOs and marketing leaders can do to buck the prediction and drive stronger results for their marketing analytics investment.

Our conversation, coupled with my own experience, solidified five ways CMOs can improve return on their marketing analytics investment, while also reinforcing why it matters:

1. Build organizational structure to apply better data

Knowing how to effectively leverage customer data and analytics is the number one success factor for CMOs today. And yet, to fully leverage the power of analytics, companies need to develop organizational structure and processes to be able to identify, combine and manage multiple sources of data.

As Golvin puts it, “companies need to build a better pipeline of carrying data from its raw state to decision and action systems for data science leaders to apply insights and powerful analysis to determine the right action and right strategy.”

To build these pathways, companies need a strong methodology coupled with an approach for how data gets aggregated, digested and applied to their various marketing systems.

2. Develop analytics leaders who bridge both data science with marketing strategy

Another key success factor for companies is developing and hiring the right leaders who can bridge both data science and business strategy. Simply put, analytics leaders need to know enough about business to ask the right questions of data. Only then, can they apply data and models to yield better decisions and drive sustainable growth.

This is our philosophy at Wharton – preparing well rounded, analytically-adept business leaders who don’t ask what data can do for them, but what data is needed to increase customer lifetime value (CLV) and how to apply data and customer insights to shape brand strategy.

Gartner regularly conducts surveys about different challenges that CMOs and marketers face, and every year, the one that rises to the top is finding skilled data and analytics leaders to hire,” shares Golvin. “Companies also struggle to find those ‘unicorns,’ or people able to command both data science and business strategy.”

Golvin also pointed out that once a company does hire an analytics leader, companies need the right foundation in place to foster their success. “There’s no value to hiring a data scientist whose output leadership doesn’t understand or know how to implement.”

Too often, we see traditional marketing organizations that aren’t able to effectively apply analytics or don’t understand how to frame the questions for data scientists on their team. The reverse is also a common challenge: analytics leaders don’t grasp how to use data to shape the broader business and brand strategy.

3. Hire a Chief Analytics Officer, or up-level the importance of analytics

So how do companies up-level the importance of analytics and develop the data-driven culture, capabilities and leaders needed to successfully transform their organization? One trend we are seeing is the emergence of the Chief Analytics Officer or Chief Data Scientist across more organizations.

As Golvin notes, “we’re already starting to see the emergence of Chief Marketing Technology Officers, who are focused on deployment of the right technology, architecture and capabilities. The next trend may be marketing analytics leaders at the c-level, who are purely about analytics and understanding the data.”

When companies empower analytics leaders to lead strategy, it can transform the culture, providing a clear vision for what customer data will be used and how to reach the desired business impact. When companies fail to make this investment, it leaves high-caliber professionals in a quandary.

“Too often data science leaders end up doing grunt work such as basic data processing and preparation, rather than using their analytics mindset and abilities to drive actionable marketing strategy, separate the signal from the noise and improve marketing outcomes,” notes Golvin.

4. Focus on better data, not big data

An ongoing challenge organizations face today is what we call “better data, not big data.” Too often we see companies that are collecting data for data’s sake, rather than taking a lean approach where they only collect data when it helps to optimize the experience for their target customers or better prediction of future behaviors.

“As data becomes more integral to marketers, a ‘more is better’ attitude develops, without necessary consideration given to the downside risks,” notes Golvin. “Companies need to do a better job of being transparent about what data they use and how, as well as considering the pros/cons, and risks of incorporating that data into a profile of their customers. More data does not necessarily lead to greater business intelligence – and in many cases can expose the brand to issues that impact customer trust.”

Data collection is in no one’s interest when it’s not meaningfully tied to strategy.

5. Separate the signal from the noise to predict and optimize business outcomes

Improving ROI for marketing analytics requires constant learning and experimentation to separate the signal from noise. There’s no better way to learn about your customer than to see what works and what doesn’t.

While big data and machine learning are great to business intelligence, a well-controlled experiment can deliver far more value. Finding the most impactful experiments to run starts with asking the right questions and maintaining a test and learn mindset where you’re constantly evolving to improve the experience for customers. The iterative adaptation based on these experiments builds momentum.

Many marketers know the “Holy Grail” phrase “deliver the right product to the right person at the right time.” In the past, this was more difficult because we didn’t know where consumers were. Now when marketers use better data, they know where the customer was and is more likely to be – providing the foundation for the ultimate in contextual 1:1 marketing.

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AdStage launches Google Sheets add-on for cross-channel campaign data

Advertisers can import data from multiple search and social adverting channels with one query.

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Now AdStage, a cross-channel campaign analytics and optimization platform, is getting in the add-on game with a new data connector for Google Sheets.

What is it? AdStage for Google Sheets, which launched Thursday, is an add-on that lets users import their paid search campaigns, social campaigns and analytics data from AdStage into Google Sheets with one query. AdStage supports paid search and social networks, including Google, Bing, LinkedIn, Facebook, Twitter and Google Analytics.

AdStage for Google Sheets has been in beta for about six months. The product pricing is based on media spend and starts at $29 per month, undercutting Supermetrics – the dominant leader in this space. The license includes unlimited users and unlimited accounts, which again challenges Supermetrics’ comparable offering.

How does it work? AdStage for Google Sheets is available from the Add-ons menu in Google Sheets. Once installed, you’ll see a sidebar in your Google Sheet. The low price means the sidebar interface isn’t fancy, and is designed for somewhat technical marketers who already know how, or are willing to learn, to build queries. The query structure is straightforward, with several query templates already available to get you started. There’s also a video training series and support portal built out for it.

Why we should care. They key is getting blended data calls to pull in data from across multiple channels with just one query. You can then build reporting dashboards in Google Sheets, like the example shown above. Or, you could bring it in to Google Data Studio. AdStage for Google Sheets uses the same API as the rest of the platform, so any data you can access in AdStage should be accessible in Google Sheets with a query.

“We are using AdStage for Google Sheets to combine cost and campaign performance data for the entire company to consume and work with. Without any integration work, we were able to aggregate all of our publisher accounts and blend complex cross-channel data into a single sheet,” said beta user Arndt Voges, head of growth at space rental company Peerspace, in a statement.

Digital agency 3Q Digital, another beta user, has already created a workbook in Google Sheets to help track and visualize cross-channel budget pacing, demographics performance and more.

This story first appeared on MarTech Today. For more on marketing technology, click here.

https://martechtoday.com/adstage-launches-google-sheets-add-on-for-cross-channel-campaign-data-232728

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Supermetrics for BigQuery launches on Google Cloud Platform Marketplace

Tired of manually connecting siloed data to create marketing reports? Supermetrics for BigQuery launches marketer-friendly solution for creating your own marketing data warehouse.

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Supermetrics for BigQuery enables marketers to bring together cross-channel marketing metrics in one platform.

Supermetrics has launched a connector for BigQuery, promising a “plug-and-play” solution for marketers to compile cross-channel campaign and analytics data with just a few clicks.

What it does. Supermetrics for BigQuery is designed to bring data from multiple marketing platforms into BigQuery — effectively setting up a BigQuery data warehouse without having to write code or SQL or rely on developer resources.

“This new product complements our existing offering by providing a robust, enterprise-scale data pipeline into the most powerful data warehouse out there, Google BigQuery,” said Mikael Thuneberg, founder and CEO of Supermetrics, in a statement.

Why we should care. The ultimate goal is to be able to make better decisions about marketing allocations faster. Getting data from multiple channels into one place where it can be analyzed is often a big headache for marketers. Eliminating the need to know how to code or write SQL, or rely on programmers and developers to create the data warehouse, means just about anyone on your marketing team might be able to get this going. Of course, you’ll need to be using BigQuery.

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Converting More Customers For The Elephants: A Homepage Analysis

Marketing for the greater good gives me the warm fuzzies, so today I’m very pleased to be running a homepage analysis for Ele and Phant — an ecommerce company that donates 30% of its profits to saving the elephants in Kenya. Before we dive in, I&…

Ele and Phant Homepage Analysis

Marketing for the greater good gives me the warm fuzzies, so today I’m very pleased to be running a homepage analysis for Ele and Phant — an ecommerce company that donates 30% of its profits to saving the elephants in Kenya. Before we dive in, I’m going to provide a little context. Here’s what their […]

The post Converting More Customers For The Elephants: A Homepage Analysis appeared first on The Daily Egg.

How To Run A Funnel Analysis For Smarter Optimization

The other day, I was speaking with a customer who was having a tough time identifying how to improve her website. This customer, let’s call her Carol, is a business owner who manages an e-commerce website focused on the design and manufacturing of reli…

how to run a conversion funnel analysis

The other day, I was speaking with a customer who was having a tough time identifying how to improve her website. This customer, let’s call her Carol, is a business owner who manages an e-commerce website focused on the design and manufacturing of reliable medical products. When I asked her what her biggest challenge was, […]

The post How To Run A Funnel Analysis For Smarter Optimization appeared first on The Daily Egg.

The new age of ‘customer’ data

The martech ecosystem needs a new class of tools for data buyers and sellers that curates and leverages date both online and offline.

The post The new age of ‘customer’ data appeared first on Marketing Land.

The martech industry seems to be constantly on the hunt for the next big thing, and understandably so. In an industry where we said goodbye to a handful of platforms and brands in 2018 (R.I.P. LittleThings, Go90s, Rocketfuel), the next big thing may be what keeps us all not only chugging along, but successful. For my big bet, I think the smart money is on an evolution of 2018’s darling, the customer data platform (CDP).

A 2018 survey by The Relevancy Group found more than 80 percent of firms had already engaged a CDP vendor or planned to. The Interactive Advertising Bureau (IAB) and Winterberry Group estimated U.S. marketers spent close to $5 billion on data management and integration products in 2018, further evidence of the market’s continued emergence.

However, leading analysts noted that 2018’s customer-data fever was limited in scope. CDPs, like data management platforms (DMPs) and demand side platforms (DSPs) before them, have a narrow focus on a specific subgroup. For CDPs, it’s brands’ existing customers. For DMPs and DSPs, it’s prospective customers, based on online intent data gathered from cookies. All of these platforms almost exclusively cater to consumer brands. I believe that in the maturing era of Big Data, there’s evidence of a new world order.

New class of data buyers and sellers

In martech’s latest epoch, consumer brands are not the only companies that curate, store, leverage and sell data. As such, they’re also not the sole purchasers of marketing technology. Publishers are just one recent example of a newer breed of data buyers and sellers coming to the table.

This new class of data buyers and sellers, already engrained in data commerce, include publishers, platforms and agency holding companies. They bring unique data challenges that CDPs, DMPs and DSPs weren’t built to solve. This new class curates data both online and offline. It also requires the ability to leverage and sell data that covers existing customers, active prospects and potential prospects yet unknown.

All of these needs require tools that offer visibility and insights into this data in ways we haven’t seen before. Data owners need technology to organize, visualize and package data sets at incredible speed and scale to activate within the martech ecosystem.

AI activation for large data sets

CDPs were bankrolled, in part, because of their ability to unify customer data and make it accessible to other systems, specifically helping brands target customers across channels and devices. Platforms, publishers and other data owners require different means of organizing and understanding the data they collect. Rather than collecting data in order to reach those users again, data owners have data that they can monetize or activate for clients, which requires an additional layer of analytics, beyond centralization and organization, in order to activate it.

The technology that we’ve already developed for the targeting use case can also serve the monetization archetype. Though it’s traditionally been used for targeting, artificial intelligence is a general activation tool for deriving insights and driving activation from large data sets, and therefore can serve both needs.

Holistic view of data management

The demand and technology exist. The timing couldn’t be better. The amount of data we create and money we spend to manage it continue to grow. But in order for our new class to embrace yet another tech stack component, three principles, scale, speed and control, must be present in the form this new platform takes.

Scale is an indelible component of marketing solutions in order to justify cost, and even more so in the automated programmatic age. Speed is integral because the longer technology takes to build, implement and start driving results, the lower the ROI. Finally, as data owners leverage new technology and data to monetize data sets, they’ll require increased visibility into data accuracy, coverage, security and more. This level of transparency shepherds an in-depth understanding of data governance practices, a requisite of an age where calls for transparency continue to crescendo in the aftermath of data-related scandals, GDPR and new stateside regulation.

The eras of Big Data, digital and single customer view have long been culminating in this new generation of holistic data management. We’ve been waiting for the technology with the capacity and range to activate this data. Now that it’s here, why should brands have all the fun? There is a new class of data owners, including publishers, platforms and agency holding companies, that can leverage this technology to bring new, unique data sets into the marketplace, which can drive incremental value across the entire ecosystem.

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Who’s Hiring in January 2019?

Here are our picks: Website Optimization Specialist – In Atlanta, SunTrust is looking for a specialist to be responsible for “developing and executing business strategies, processes and policies to enhance the sales and service experiences intrinsic to SunTrust’s digital spaces.” A/B Testing & Personalization Analyst – Join Barnes & Noble’s Optimization team in New York […]

The post Who’s Hiring in January 2019? appeared first on Brooks Bell.

Here are our picks:

Website Optimization Specialist – In Atlanta, SunTrust is looking for a specialist to be responsible for “developing and executing business strategies, processes and policies to enhance the sales and service experiences intrinsic to SunTrust’s digital spaces.”

A/B Testing & Personalization Analyst – Join Barnes & Noble’s Optimization team in New York to “improve bn.com’s content, design, and usability for customers and to create unique experiences based on customers’ preferences and behaviors.”

Director-Digital Product Analytics & Testing –  Join the Enterprise Digital and Analytics team at American Express in New York.  They are looking for a leader to “provide value to the online card shopping experiences within the Global Consumer and Commercial businesses through customer data and measurement, insights through analytics techniques and experimentation.”

Marketing Manager, International Conversion – Ancestry is looking for a candidate to join their Conversion Marketing team in San Francisco.  This person is “responsible for improving and optimizing the user experience at each step in the conversion funnel with the end goal of maximizing revenue from visitors in each of Ancestry’s key global markets.”

Marketing Manager, A/B Testing & Optimization – Join AuthO’s Growth Team in “driving improvement in key engagement metrics and customer experience throughout the customer lifecycle.”

Director of B2B Marketing, Demand Generation – Join Vimeo’s B2B marketing team in New York to “scale qualified lead acquisition, build and continuously optimize digital marketing, account-based marketing (ABM), email automation, social, and event-based marketing channels.”

Sr. Analyst, eCommerce Direct to Consumer Analytics – Newell Brands is looking for a senior analyst in Hoboken, New Jersey, to drive “sustainable growth online through the best-in-class use of data and analytics.”

Digital Marketing Leader – Website Optimization – Join GE Healthcare in Wauwatosa, Wisconsin to “develop a rigorous testing and experimentation framework, and conceive, scope and implement experimentation initiatives to improve the website user experience and drive conversion rate optimization.”

Manager, Marketing Planning, Test & Analysis – Express is looking for an individual to lead the testing and optimization program in Columbus, Ohio, “starting with A/B & multivariate testing taking us into experience optimization and eventually personalization.”

 

Looking for a job or to fill a position?  Give us a shout and we’ll help spread the word in our next careers blog post.

 

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Building the essential marketing technology stack to fuel your experimentation program

We hear shouts of “hyper-personalization” constantly—a one-to-one customer experience is the pinnacle for many organizations today. Of course, this relies…Read blog postabout:Building the essential marketing technology stack to fuel your experimentat…

We hear shouts of “hyper-personalization” constantly—a one-to-one customer experience is the pinnacle for many organizations today. Of course, this relies...Read blog postabout:Building the essential marketing technology stack to fuel your experimentation program

The post Building the essential marketing technology stack to fuel your experimentation program appeared first on WiderFunnel Conversion Optimization.

Free Guide: How to Strategize & Execute Profitable Personalization Campaigns

When I speak with our clients, it often strikes me how many of them feel overwhelmed by the very idea of personalization. Our imagination, often fueled by the marketing teams of various software companies, creates a perfect world where personalization enables every interaction to be completely custom for every individual. In this dreamland, artificial intelligence […]

The post Free Guide: How to Strategize & Execute Profitable Personalization Campaigns appeared first on Brooks Bell.

When I speak with our clients, it often strikes me how many of them feel overwhelmed by the very idea of personalization.

Our imagination, often fueled by the marketing teams of various software companies, creates a perfect world where personalization enables every interaction to be completely custom for every individual. In this dreamland, artificial intelligence and machine learning solve all our problems. All you have to do is buy a new piece of software, turn it on, and…BOOM: 1:1 personalization.

As a data scientist, I’ll let you in on a little secret: that software only provides the technological capability for personalization. Even further, the algorithms found within these tools simply assign a probability to each potential experience that maximizes the desired outcome, given the data they have access to. Suffice to say, they’re not as intelligent as you are led to believe.

If you caught our first post in this series, you already know that we define personalization a bit more broadly, as any differentiated experience that is delivered to a user based on known data about that user. This means personalization exists on a spectrum: it can be one-to-many, one-to-few, or one-to-one.

And while there are many tools that enable you to do personalization from a technical standpoint, they don’t solve for one of the main sources of anxiety around personalization: strategy

Most personalization campaigns fail because of a lack of a strategy that defines who, where and how to personalize. So I’ve put together a free downloadable guide to help you do just that. This seven-page guide is packed full of guidelines, templates and best practices to strategize and launch a successful personalization campaign, including:

  • Major considerations and things to keep in mind when developing your personalization strategy.
  • More than 30 data-driven questions about your customers to identify campaign opportunities.
  • A template for organizing and planning your personalization campaigns.
  • Guidelines for determining whether to deliver your campaigns via rule-based targeting or algorithmic targeting.

Free Download: Plan & Launch Profitable Personalization Campaigns.

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Thank You + Brooks Bell’s Best of 2018

It’s January 3, and if you’re like us, you’re already heads down at your desk and neck deep in emails. But we’d be remiss if we didn’t take a minute to reflect on the previous year. In November of 2018, we quietly celebrated 15 years of being in business. When Brooks Bell was founded, experimentation was in […]

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It’s January 3, and if you’re like us, you’re already heads down at your desk and neck deep in emails. But we’d be remiss if we didn’t take a minute to reflect on the previous year.

In November of 2018, we quietly celebrated 15 years of being in business. When Brooks Bell was founded, experimentation was in its infancy. But despite all the changes we’ve experienced since then, one thing remains true: it is the opportunity to connect with so many interesting people that are solving big problems for their business that makes our work worthwhile. Thanks for walking with us.

A look back at some of our big moments from 2018

Winning like Winona

In January, our Founder & CEO, Brooks Bell, was recognized as one of 25 women who rocked digital marketing in 2017. Later in the year, she was also announced as a Southeastern Finalist for EY’s Entrepreneur of the Year award. 

We also celebrated 2017’s record-breaking growth, were recognized as Optimizely’s North American Partner of the Year, and we garnered our local business journal’s Best Places to Work award.

Getting Lit with Illuminate

Fun fact: We originally built Illuminate to help us better manage and iterate upon our clients’ tests. Over time, we got so much great feedback, that we decided to make it available to everyone this year.

Now, with a successful beta launch under our belt and even more new features being added to the software, we’re excited to see where this new endeavor takes us in 2019.

F is for Friends, Fun and…Fear?

In October, things got a little spooky around the office and it had everything to do with Scott, our Director of Sales, who decided to channel his inner Ellen Degeneres for the day (much to our colleagues’ horror). Watch the video if you dare.

Making Bacon for our Clients

Back in 2014, we set a Big Hairy Audacious Goal to achieve $1 billion in projected revenue for our clients. By the end of 2017, we’d reached $500 million. And this past December, we hit $1 billion. (cue ::gong::)

But we’re not resting on our laurels. We’ve set some aggressive goals for 2019, with a focus on personalization, and we’re pumped to get to work.

Brooks Bell takes the Bay Area 

In September, we officially opened the doors to our San Fransisco office. This decision came after years of working with clients on the West Coast and our desire to work even more closely with them. And with the Bay Area’s rich history of innovation, we can’t think of a better place to help more companies push their boundaries through experimentation.

Still Clickin’ 

Last May, we hosted our annual Click Summit conference. We might be biased but this remains one of our favorite events as it’s filled with meaningful connections and seriously impactful takeaways. 2019 marks our 10th Click Summit, and we’ve got big plans. Request your invite today.

2018 on the blog

 


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