THE 2019 NO B.S. BUYERS GUIDE FOR MARKETING ANALYTICS Alight Analytics | The 2019 No B.S. Buyers Guide for Marketing Analytics 3 Maybe you downloaded this guide because you’re searching

THE 2019 NO B.S. BUYERS GUIDE FOR MARKETING ANALYTICS

[email protected] | 816.359.3305 | www.alightanalytics.com

Alight Analytics | The 2019 No B.S. Buyers Guide for Marketing Analytics 2

WHAT’S IN THIS GUIDE

Introduction 3

How to Find the Right Analytics Solution 4Four Levels of Marketing Analytics Performance 4Five Types of Marketing Analytics Technology 5Six Marketing Analytics Roles 6

Investing Strategies by Performance Level 7Level 1: Understanding What Happened 7Level 2: Understanding Channel & Campaign Performance 10Level 3: Understanding How Marketing Creates Value 13Level 4: Understanding What to Do Next 17

What to Ask Before Buying a Marketing Analytics Solution 20


Maybe you downloaded this guide because you’re searching for a marketing analytics platform that can deliver eye-opening business insights and fast, accurate performance reports.

Or maybe your goals are more modest. If it’s not too much trouble, you would like to buy marketing analytics software that doesn’t turn your job into a tear-soaked hellscape of frustration.

Either way, we’ve been exactly where you are. And we’re going to help you find an analytics solution that does exactly what you need it to do.

INTRODUCTION

Who are we, and why should you care?

Alight Analytics has been practicing marketing analytics for more than a decade, even before anyone really knew what “marketing analytics” was. We help the world’s most successful enterprises and agencies to prove their marketing efforts deliver real and measurable value.

That means we’ve helped clients create gorgeous dashboards, build sophisticated media mix models and perform cross-channel attribution. But early on, we also had to cobble together performance reports by hand, armed with nothing more than Excel and PowerPoint. We know how powerful and how challenging marketing data can be.

To solve our own data problem, we tried and tested pretty much every solution available. Nothing quite worked for us. So we ended up developing our own platform, ChannelMix, to automatically aggregate, cleanse and store any type of marketing, media and sales data.

Why should you read this guide?

Shopping for a marketing analytics solution is difficult because there are dozens of options on the market today. Many of them are

powerful and well-designed, but nobody has built the perfect, all-purpose tool that works for every single marketer. And that makes sense: Every organization has different needs and different goals.

So instead of rating and ranking specific pieces of software, this guide will:

• Help you identify what’s most important to your organization, so you can find the right solution for your unique marketing analytics needs.

• Highlight the most common types of solutions on the market — including their pros, cons and capabilities.

• Show you the most important questions to ask when considering a new platform, so you can get the greatest value for your money.

Ready to cut through the confusion and find a solution that actually works for your team?

Let’s get started.

6,829marketing technology solutions available in

2018, up 27 percent from 2017

Source: Martech 5000 (2018)


A BETTER STRATEGY FOR FINDING THE RIGHT MARKETING ANALYTICS SOLUTION

1. Determine where you are and where you want to go.

Are you spending too much time collecting and organizing your data? Struggling to justify your marketing spend to your boss or clients? Or maybe you’re eager to do the really cool stuff, like media mix modeling and cross-channel attribution.

The 4 Levels of Marketing Analytics Performance can help you find the way forward. It’s a framework we developed for:

• Diagnosing your current analytics capacity and needs.

• Investigating the potential benefits and demands of more advanced levels of analytics.

• Learning what’s necessary to progress to the next stage of analytics maturity.

In the coming pages, you’ll see how the 4 Levels represent the evolution that marketers experience as they develop their ability to produce marketing analytics. Levels 1 and 2 are focused on understanding past performance, while Levels 3 and 4 empower marketers to make decisions going forward.

As you encounter each Level, ask yourself which one reflects your present situation — and which one represents where you want to go. It’s important to be as specific and clear as possible about these two points, so you can (A) select the correct platform for your team and (B) make sure you have the correct people in place to use it.

REPORTING (What Happened)

ANALYTICS (What To Do)

LEVEL 1

LEVEL 2

LEVEL 3

LEVEL 4

Basic automated reporting by

marketing source.

Reporting on performance across

channels and campaigns.

Understanding channel value to

optimize spend and maximize results.

Predicting the right media mix and

forecasting ROI for all channels.

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Single-Stack Solutions: With a single-stack solution, you can aggregate, organize, store and analyze your marketing data with just one platform. There are real benefits to a single-stack approach — for starters, everything is centralized, which may allow you to get up and running faster.

Single-stack tools also tend to have more out-of-the-box data connections and sharper looking visualizations than basic dashboard and hybrid tools, but they still require support and human intervention.

Full-Stack Solutions: In a full-stack setup, you use the best tool for each step of the analytics process. It will require a bigger upfront investment, but it’s also the most adaptable, powerful choice.

For starters, you’ll need a platform that can automatically aggregate, cleanse and organize marketing data. You’ll also need a place to store that data, such as a data warehouse, either internal or an external one managed for you. Or you could use some other form of cloud-based data storage. (Some solutions, like ChannelMix, offer both aggregation and storage.)

And finally, you’ll need a BI or visualization tool — and possibly a statistical modeling solution — that can help you analyze your data and create reports or visualizations.

2. Select the correct technology for your goals and needs.

Most marketing analytics platforms and software tend to fall into one of the five following classes. There’s no single “best choice” — rather, each could be a top performer under the right circumstances.

Connector Tools: A connector tool automates the collection of data from popular sources such as Facebook and Google Analytics. The connector then pushes that data into a spreadsheet like Excel or Google Sheets. You can usually create some basic charts and graphs with the spreadsheet application’s built-in tools.

Basic Dashboard Tools: These are solutions that pull performance data from a source and plug it directly into a visualization. You can create attractive dashboards with these tools, though you may lack the ability to customize the design exactly how you wish. With dashboard tools, data typically lives in the originating source (Facebook, Google, etc.).

Hybrid Tools: This category blends the capabilities of connectors and basic dashboard tools. You can push marketing data to a spreadsheet app and visualize it with the hybrid tool itself. Hybrids often don’t come with their own storage solution.

CONNECTORS DASHBOARDS HYBRID SINGLE-STACK

AGGREGATION & STORAGE

STORAGE

VISUALIZATION

FULL-STACKAGGREGATION

STATISTICAL MODELING


3. Ensure you have the people to support your practice.

Technology is important, but it’s not the only thing that dictates the success of an analytics program. You’ll also need people who can use it to produce high-quality reporting and actionable insights. There are six specific roles that contribute to a healthy, high-functioning marketing analytics practice.

Two things to note: You won’t need all six roles at each level. And just because there are six roles doesn’t mean you need six people — in some cases, one person might be able to handle more than one role.

Analyst: The person responsible for executing your reporting and visualization strategy.

Data Engineer: The team member who

manages the marketing data — from making connections with data sources to building views of the data.

Data Scientist: This team member uses modeling and attribution solutions to uncover patterns and insights in marketing data.

Influencer: A change agent, someone who can influence the larger organization’s processes and culture — especially when it comes to fighting for budget and resources for analytics.

Solution Design: The person who oversees data flow and ensures your analytics solution is scalable and efficient. (This person’s title might be solution architect or data strategist.)

Marketing Strategist: A data-driven marketer who uses robust analytics to plan campaigns, arrange media buys and contribute to the bottom line.

BUSINESS STRATEGY

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The 4 Levels of Marketing Analytics performance lay the groundwork for your marketing strategy. Once you understand your current and desired level, you will have a framework for where you need to invest. In the following sections, we’ll go in depth into each level and the marketing analytics technology and roles you’ll need for success.


LEVEL 1: UNDERSTANDING WHAT HAPPENED“How many people visited our website? How many clicks and impressions did we get last month?”

What does Level 1 look like?

At this level, marketing teams are simply trying to figure out what happened. The focus is not on analysis and business insights, but meat-and-potatoes reporting.

In most cases, Level 1 marketers are tracking activity from a handful of popular data sources like Google Analytics or Facebook. Even so, downloading data from each of those platforms and getting them into a report can be a time-consuming process.

Many Level 1 marketers try to solve this problem with some form of reporting automation — a tool that will take data directly from the source and feed it into a spreadsheet or dashboard.

Even with these tools, Level 1 teams typically

spend 70 percent of their time on data preparation and management, compared to 30 percent for reporting and analysis.

Solutions at this level tend to be relatively inexpensive. The software usually has less functionality than you’ll find at Levels 2, 3 or 4, but depending on your situation, that may not be an issue. A small ad agency that only utilizes a few popular data sources, for example, might meet all its needs with a reporting automation tool.

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Example of a Level 1 dashboard

BASIC AUTOMATED REPORTING BY MARKETING SOURCE

SEARCH PPC SOCIAL


Where do you need to invest?

TECHNOLOGY If you’re simply putting together basic performance reports, then connectors and basic dashboard tools can do the job. Connectors automatically take data from platforms like Facebook and Google Analytics and store it in a spreadsheet.

A basic dashboard tool will instead feed the data into a dashboard, though it typically doesn’t offer any storage — all the data continues to reside in the originating platform. That means you won’t be able to apply business rules or clean up errors in the data before it appears in your dashboard.

Both connectors and basic dashboard tools will help you track your performance on essential metrics like clicks or sessions. Plus, using them is faster and more accurate than building reports manually.

But there’s a ceiling to what you can accomplish at Level 1. If you plan to someday

LEVEL 1

LEVEL 2

LEVEL 3

LEVEL 4CONNECTORS

DASHBOARDS

STRATEGISTANALYST

use a wider variety of media sources or offer more advanced analytics, like forecasting or attribution or even reporting across campaigns and channels, then connectors and basic dashboard tools won’t get you there. And you’ll have to reboot a big part of your analytics practice when you outgrow them.

ROLES For Level 1, you’ll need the following roles:

Analyst: Because Level 1 is all about reporting, you must have someone who can oversee reporting. At this stage, analysts are most likely building reports and dashboards themselves.

Marketing Strategist: This is someone who can take those reports and highlight important findings for clients or stakeholders. (If the team is small, the analyst and the marketing strategist might be the same person.)


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Am I ready for Level 2?• Do you need to track results for several data sources?

• Do you need to view your results by campaign or channel?

• Do you want to provide actionable insights to clients?

• Do you need a more flexible, more powerful way to communicate results to clients and stakeholders?

What does Level 1 require?

• A need to provide basic “what happened when” reporting, but not detailed business insights.

• A tool for automating the collection of marketing data.

• A relatively small data ecosystem that focuses on the most popular data sources.

• A team member who can take responsibility for data preparation and management, including automating reporting.

What can you do at Level 1?

• You can provide basic, activity-based tracking for a few popular data sources, such as Google Analytics or Google Ads. One thing to note: If you need to pull from a data source that isn’t part of the solution’s existing API library, you may be responsible for setting up that connection on your own.

• You can quickly see how each data source is performing.

• Depending on your solution, you’ll be able to create basic dashboards. If you’re using a connector tool, you’ll only be able to use the spreadsheet’s built-in tools for charts and graphs.

• In many cases you can easily push data to Excel or Google Sheets, a good solution for smaller, less complex datasets.

What can’t you do at Level 1?

• You may not have the time or capacity to deliver more sophisticated insights — for example, showing which data sources contributed to conversions.

• Campaign-based or channel-level analysis may not be possible because each data source will still exist in its own silo. (For example, you could only look at your Facebook results in isolation rather than combined with another source like Google Ads.)


LEVEL 2: UNDERSTANDING CHANNEL & CAMPAIGN PERFORMANCE “How is our paid social channel doing? How many new leads did last month’s campaign generate?”


At Level 2, the focus is still on reporting, but you’re using a more sophisticated lens to examine your data.

It’s not enough to measure the activity of individual data sources, one by one. You need to understand how multiple sources work together.

For example, you’ll probably want to study the performance of entire channels — that is, groupings of similar data sources like paid search (Google, Bing, Yahoo Search) or organic social (Facebook, Twitter, Snapchat) or traditional offline media (TV, radio, print) — so you can determine which strategies are most effective.

It’ll be important to study results by campaign, too. How did Facebook, TV, Google Ads and other sources all work together to promote the big back-to-school sale?

To understand the performance of an entire channel or campaign, you must create one view that combines multiple data sources for easy review. In the Level 2 dashboard example on the next page, you can see each channel’s contribution to overall goals and how it compares to other channels.

Be careful: There are many platforms that promise to organize data by campaign or channel for you. In practice, it can be more

complicated. That’s because different data sources often employ different taxonomies — they have different ways of naming campaigns or using dates. The data sources must be normalized, or the combined view will be inaccurate or unintelligible.

Your platform may or may not be able to do this for you. Because there are so many different data sources, each with their own idiosyncratic way of doing things, getting them aligned frequently takes human intervention.

Can you join and blend datasets by hand, normalizing the taxonomy as you go? Yes. But your team could end up spending 50 percent of its workweek building (and cleaning up) blended views of your data.

Level 2 analytics solutions usually give you more power to visualize data, but there are also greater demands placed upon you, the user. For starters, visualization takes time to learn. It’s one of the best ways to communicate your results quickly to large audiences, but you’ll need to master another skill set.

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REPORTING ON PERFORMANCE ACROSS CHANNELS AND CAMPAIGNS

PPC SOCIALSEARCH



TECHNOLOGY Hybrid and single-stack solutions are built for Level 2 reporting. A single-stack solution allows you to aggregate, store and visualize your data with a single platform. A hybrid, meanwhile, allows you to visualize data that you pull from a spreadsheet — a combination of connector and basic dashboard tools.

With hybrid and single-stack platforms, you’ll have a greater ability to bring together data from multiple sources to create campaign-

wide or cross-channel datasets. And you should have more power to customize your dashboards and visualizations. Plus, everything you were doing at Level 1? Level 2 tools can do that, too.

Blending datasets together won’t always be easy — again, some human intervention may be required. But hybrid and single-stack can at least do something here. Connector and basic dashboards tools just can’t.

ROLES

Analyst: At Level 2, the analyst is usually responsible for building more complex reports and visualizations, so it’s important for them to spend as little time as possible struggling with data management.

Marketing Strategist: Cross-channel reporting can give you bigger clues about what is and isn’t working in your campaigns. You need the marketing strategist to notice these trends and use the data to guide spending decisions.

Data Engineer: Level 2 tools usually come with more out-of-the-box connections to data sources, but they always seem to miss the one source you absolutely positively must have. The data engineer finds a way to get your wayward data into the platform, whether that involves an API, a file upload or some other method.


LEVEL 1 LEVEL 2

LEVEL 3

LEVEL 4

STRATEGISTANALYST

SINGLE-STACKHYBRID

DATA ENGINEER


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https://public.tableau.com/profile/alight.analytics#!/vizhome/MediaDashboardExample/MediaReport



• You are tracking and measuring several data sources, and you need to combine those sources in a single view at the campaign or channel level.

• You have a person, either internal or external, who can spend up to half their time on data preparation and management.

• You have someone, either internal or external, who has the ability to create visualizations.


• You can measure performance at the campaign, channel or promotion level.

• You can usually access a wider library of API connections to incorporate more media sources.

• You can create more customized visualizations and dashboards.


• Your team may have to manage your own data connections and make repairs when necessary. You also might not be able to access all data sources, especially niche or offline channels, unless you have someone who can set up and manage those connections (most likely they will need to know how to write code).

• Depending on your platform or source, you may have to blend data sources into a single dataset on your own.

• You probably won’t be able to view marketing performance by product, customer or market segments unique to your business or industry.

• You may not be able to customize your visualization exactly how you wish. When using a single-stack or hybrid tool, visualization is often template-based.

Am I ready for Level 3?

• Do you need to show how marketing activity across multiple channels worked together to create ROI and increase sales?

• Do you need more power to customize how your visualizations look and function?

• Do you have a common tracking strategy in place across all data sources?

• Do you already have a mature, operational stack of marketing analytics solutions for data aggregation and management, storage and BI/visualization?

• Do you have buy-in from your leadership? Are they willing to use marketing analytics to guide strategy?


LEVEL 3: UNDERSTANDING HOW MARKETING CREATES VALUE“Does our digital advertising drive in-store purchases? How does our latest campaign compare to past campaigns?”


You start to see which marketing activities are generating leads, driving sales and helping you achieve other business goals. When someone makes a purchase on your website, you’ll know if they saw your last email, your search ad, your latest TV spot. Once you know that, you can optimize your ad spend in real time, so you can do more of what works, ASAP.

You’ll also possess the ability to incorporate contextual and historical data into your analysis.

For example, if you have the right data, you can benchmark your results against your own past performance, your competitors and your overall industry. Or you could tell how your latest campaign’s results are pacing against the goals and budget you set for it.

This represents a shift from Level 1 or 2, where you’re mostly trying to figure out what’s already happened. At Level 3, you’re actively using data to make decisions going forward.

In the Level 3 dashboard example on the next page, you can segment by geography and get a wealth of information on marketing performance up and down the funnel, along with insight into sales. That could clue you into regions that are underperforming and

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are opportunities for increased marketing investment.

Or it could give you the information you need to have a business discussion with a territory manager — there might be a problem in operations or customer service. (You could do similar segmentation by line of business or product, too.)

Achieving Level 3 insight requires a more disciplined approach to your data and more preparation when building campaigns and allocating spend.

In addition to using a common taxonomy across data sources, you’ll need a solution that supports a common tracking methodology and, where possible, allows you to attach contextual data to the tracking — for example, the total budget or goals for a specific campaign.

Level 3 marketers typically spend just 20 percent of their time on data preparation.

UNDERSTANDING CHANNEL VALUE TO OPTIMIZE SPEND AND MAXIMIZE RESULTS

PRODUCT SEGMENT

SEARCH

PPC

SOCIAL

CRM

TV

MARKET SEGMENT

CUSTOMER SEGMENT

TARGETED INSIGHT



TECHNOLOGY At Level 3, a full-stack approach makes the most sense here. For a full-stack solution, you’ll need separate tools for data aggregation, data storage and business intelligence or visualization. (Some tools, like ChannelMix, combine aggregation and storage.)

Full-stack’s key benefit is the ability to use the best possible solution at each step of the process. And that’s important at Level 3 because you’ll undertake more sophisticated analysis involving multiple complex datasets. You need solutions that can take anything you throw at them. A full-stack solution can do everything you were doing at Levels 1 and 2.

With a full-stack strategy, you’re not locked in: If a better BI or viz tool comes along, you can use your data on that new platform. That’s different from some Level 2 tools, which make it harder to move your data to other platforms or storage solutions.

ROLES

Analyst: Visualizations become more important and sophisticated, and the tools used to create them become more complex. You need a dedicated analyst for Level 3.

Marketing Strategist: Like the analyst, the marketing strategist is tackling more complex work, so that person needs to spend as little time as possible on direct data management.

Data Engineer: A full-stack approach will require more support — including managing the organization’s data warehouse, setting up data connections and performing any maintenance or repairs. For larger organizations, it could make sense to hire a full-time employee for that role. Smaller organizations, especially ones that don’t already have a big IT or development team, might be better off outsourcing some or all of those functions to a third party.

Solution Design: You’ll be working with more complex sources of data at Level 3, so you need someone who can set up datasets correctly and ensure that data continues to move into the platform. Sad but true: Data connections sometimes fail, so it’s important to have someone who can troubleshoot.

Influencer: A Level 3 practice will produce insights that can guide not just marketing, but strategy for the larger organization, especially if you can layer sales and transactional data into your analytics. An influencer will present your findings to the organization’s leadership and make the case for using marketing analytics in decision-making.


35.8%how often CMOs say marketing analytics is

used for decision-making

Source: CMO Survey (August 2018)

https://public.tableau.com/profile/alight.analytics#!/vizhome/MarketingOppOfficePerformance/MarketingOpportunity



• Well-structured marketing, media and sales data, normalized and stored in an actively managed data solution.

• A person, either internal or external, who can take responsibility for setting up, managing, cleaning and repairing your datasets and connections.

• A person, either internal or external, who uses a BI or visualization tool to create reports and analysis.

• Buy-in from your company’s leadership. They’re committed to using marketing analytics to guide their decisions in marketing and beyond.


• You can attribute campaign results to spend across multiple channels. If a customer makes an in-store purchase, you’ll know if that person saw your emails, TV commercials and digital ads along the way.

• You can connect to all your data sources, no matter how popular or niche, including sources of sales and offline data.

• You can now segment by customer, product, line of business or geography, and see how they connect to funnel activity.

• You have the ability to optimize spend, even while the campaign is ongoing.

• You can manage large and complicated datasets.

• You can have very high levels of customization.


• You usually can’t produce Level 3 analytics quickly. You’ll have invest time to set up your framework.

• You can’t create forecasts that project how much value your spend will create in the future.

LEVEL 1 LEVEL 2 LEVEL 3

LEVEL 4

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Am I ready for Level 4?

• Do you need a systematic way to forecast how much spend is required to achieve business goals?

• Do you need to predict the optimal spend for multiple regions or business segments?

• Do you already have a mature, operational stack of marketing analytics solutions for data aggregation and management, storage and BI/visualization?

• Do you have buy-in from your leadership? Are they willing to use marketing analytics to guide strategy?


LEVEL 4: UNDERSTANDING WHAT TO DO NEXT“How much do we need to spend on marketing to grow the business by 30 percent next year? Which leads are most likely to become customers? Which customer segments are most receptive to upsells — and what do they want to buy?”


For most marketers, Level 4 is the promised land. At this point, data isn’t just telling you what you did and what happened. It will tell what you should do and what you can reasonably expect to happen, based on past performance.

Say you’re creating a media plan for next quarter. At Level 4, you can build a calculator that shows you where, when and how much to spend, market by market, even down to the ZIP code. You’ll even be able to project how many new conversions you can expect from that level of investment.

Wish your sales team were able to close more deals faster? You can determine which leads look most like your best current customers — and, thus, are more likely to become customers — so your sales reps can devote more time and attention to those prospects.

You’ll gain deeper insight into customer behavior. You’ll know which customers are most likely to leave and when, whether they’re open to upsells and cross-sells and what types of offers and content are most effective in persuading them to convert. You can identify new customer segments and identify the messages that resonate most strongly with them.

Level 4’s impact ripples beyond the marketing

department. You know more about what, where and when customers are buying — intelligence that should be very interesting to the teams that oversee your supply chain or plan new store locations. It could even influence the decision to launch or close lines of business.

This is what we mean when we say marketing analytics is a strategy. Level 4 analytics isn’t a rearview mirror; it’s a crystal ball.

All of this is possible only because you have a deep, well-maintained storehouse of data — not just marketing data, but sales data, supplemented with sources that look at weather, geography, social sentiment and more.

Level 4 marketers spend only 10 percent of their time on data preparation, but only because they’ve turned that responsibility over to an internal or external specialist. The work is so complex that it has to be overseen by a dedicated professional.

PREDICTING THE RIGHT MEDIA MIX AND FORECASTING ROI FOR ALL CHANNELS

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A Level 4 analytics practice is built on a complete, stable framework for producing marketing analytics. It employs a BI or visualization tool drawing from a data warehouse or some other data storage solution, either internal or external. A data aggregation and management solution ties everything together. Anything you did at Level 1, 2 or 3, you can do at Level 4.

Like Level 3, here you have the power to use a stack of the best-in-breed solutions, the ones that make sense for your organization. You’ll need the power and flexibility that come with dedicated solutions.

Level 4 also requires intentional oversight. Unlike the standard reporting of Level 1, it’s not something that can be set up and left to run. To get the full value from the investment, leadership must also treat it as a strategy, a way to guide important business decisions.

While Level 4 is the desired outcome for many organizations, it’s not right, necessary or even possible for everyone. You may find that your needs are satisfied by practicing marketing analytics at Level 3, 2 or 1.


TECHNOLOGY Level 4 takes the full stack of solutions (data


aggregation, data storage, BI or visualization) and adds a statistical programming language and environment such as R or SAS. (Simple models can be run inside some BI tools, but you’ll probably need a dedicated platform for deploying your models.) When buying a data warehouse or other storage solution, ask if it supports the inclusion of statistical modeling languages, either as a standard part of the product offering or as an add-on.

One thing to note: There are several tools that promise “automated” insights, usually through some form of machine learning. In many cases, these insights are based on a single data source. Advanced analytics should draw from complex datasets, those built from multiple data sources and living in an actively managed data warehouse.

ROLES Analyst, Marketing Strategist, Data Engineer, Solution Design, Influencer: Level 4 is the highest possible form of marketing analytics. To do it right, you’re going to need the whole team, including the addition of a …

Data Scientist: Because of the complexity involved, Level 4 also requires a data scientist, someone who can build models and find underlying patterns in your data. (This person may be called a senior analyst.)


What Does Level 4 Require?

• You’ll need larger, more complex datasets that can be used to forecast potential results and guide spending.

• You’ll need a full-stack solution that incorporates modeling languages.

• You’ll need a team that incorporates each of the six roles, especially when it comes to managing your data and setting up and running any statistical models.

What You Can Do at Level 4

• You can build models that allow you to forecast how many conversions or sales you can reasonably expect from a certain level of spend.

• You can build calculators that help you find the most effective level of spend and channel mix based on location, seasonality and other factors.

• You have the ability to push your data to other platforms or storage solutions — an important capability for marketing teams at larger enterprises.

What You Can’t Do at Level 4

• You can’t “set it and forget it.” Because this is the most complex version of marketing analytics, you’ll need time, money and human talent to establish and maintain a Level 4 stack of solutions.

• Marketers can’t (and shouldn’t) take direct responsibility for data management. That needs to be handed over to an internal or external specialist.

LEVEL 1 LEVEL 2 LEVEL 3 LEVEL 4

SOLUTION DESIGN

INFLUENCERSTRATEGISTANALYST DATA ENGINEER

DATA SCIENTIST

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WHAT TO ASK BEFORE BUYING MARKETING ANALYTICS SOFTWARE


Level 1+

How much time does it take to use this tool? Will I need to dedicate a staff member to managing and supporting this tool? What percentage of their workweek will be spent operating this platform?

How does the solution store aggregated data? Does it offer a data warehouse where I can store my data? If I need to, how can I push that data to other platforms or storage solutions?

Can my analytics solution automatically collect data from all my sources of marketing data? Does the solution offer other ways (beyond APIs) to bring data into its system, such as direct file uploads?

If a data connection fails or breaks, who is responsible for repairing it? Will the solution alert me if a failure occurs?

Level 2+

Will this solution automatically blend my data sources together? Do I have access to a person, either internally or externally, who can handle this task?

Alight Analytics | The 2019 No B.S. Buyers Guide for Marketing Analytics 21Alight Analytics | The 2019 No B.S. Buyers Guide for Marketing Analytics 21

Does the solution offer BI or visualization capabilities? Will it “play nicely” with dedicated, third-party BI or visualization tools?

Level 3+

Does the solution support a common tracking methodology, so I can understand the value of each channel or campaign? Will it help me normalize my disparate campaign names across my entire media plan?

Will I be able to bring additional contextual data — including sales and transactional data, budget and goals — into the solution? How will this additional data be added? What if I need to change it or export it?

Level 4+

If I want to produce forecasts and other Level 4 analytics, do I have people on staff — or does my vendor have people on staff — who know how to use R and other statistical modeling languages? Do those people also understand marketing strategies, media data and related terminology?

Does my database architecture support the inclusion of these statistical modeling languages, especially for custom situations? Is that a standard part of the product offering, or is there an additional charge?

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BEST-IN-CLASS DATA AGGREGATION

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OUR TEAM IS YOUR TEAMChannelMix comes with the expertise of our entire team of data engineers, analysts, scientists and solution designers.

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Integrate with your choice of business intelligence and visualization tools. Your data lives in a warehouse that’s managed by our experts.

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Bring together marketing, media and sales data from any source and generate analysis-ready datasets for any level of analytics.

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REPORTING & ANALYSIS

Any modeling tool you want

MEDIA SOURCES

Mail Sales

Display PhoneTVSocialWebCRM

EmailRadioOOHSearch

Client-facing dashboards

Any BI tool you want

Documents

THE 2019 NO B.S. BUYERS GUIDE FOR MARKETING ANALYTICS Alight Analytics | The 2019 No B.S. Buyers Guide for Marketing Analytics 3 Maybe you downloaded this guide because you’re searching