From funnel to flywheel

If you’re like most marketers, you could name the basic parts of the sales funnel in your sleep: Awareness, Interest, Evaluation, Decision, and Purchase. Of course, businesses have tweaked the model over the years, adding extra steps and so forth, but the basic premise has remained the same. But there is one problem with the […]

The post From funnel to flywheel appeared first on Marketing Land.

If you’re like most marketers, you could name the basic parts of the sales funnel in your sleep: Awareness, Interest, Evaluation, Decision, and Purchase.

Of course, businesses have tweaked the model over the years, adding extra steps and so forth, but the basic premise has remained the same. But there is one problem with the model: it’s the opposite of customer-centric. In fact, in the traditional sales funnel, leads are treated a bit like uniform widgets moving along a conveyor belt, with various things happening to them along the way.

The problem is that if you’re not centered on the customer, your marketing efforts might be going to waste. If we had a nickel for every brilliant content strategy that seemed to explode with engagement while yielding little (if any) measurable return on investment, we’d have more than a piggy-bank full of change.

Centering the customer in your sales model changes that, though, because the customer now drives all content and all marketing efforts, instead of the other way around. In this piece, we’ll explain a new sales model. Maybe by the end you’ll be like us: falling ever-so-slightly out of love with the funnel — and in love with the flywheel.

A what wheel?

Like its predecessor the funnel, a flywheel is not just a metaphor, but also a real-life tool that powers multiple, modern-day inventions. Invented by James Watt of lightbulb fame, the flywheel is a disc or wheel around an axis. It has assorted industrial applications and can be found in car engines, ships, and a lot of other places where energy needs to be generated, amplified, stored, and stabilized.

The flywheel effect, described by Jim Collins in his book, Good to Great, describes a massive, 5,000-pound metal disc mounted horizontally on an axle. He asks the reader to imagine pushing it, so that it turns around that axle. At first, getting it to move at all is extremely difficult. But with each push, it gets fractionally easier and the flywheel begins to pick up speed. Collins writes:

Then, at some point—breakthrough! The momentum of the thing kicks in in your favor, hurling the flywheel forward, turn after turn … whoosh! … its own heavy weight working for you. You’re pushing no harder than during the first rotation, but the flywheel goes faster and faster. Each turn of the flywheel builds upon work done earlier, compounding your investment of effort. A thousand times faster, then ten thousand, then a hundred thousand. The huge heavy disk flies forward, with almost unstoppable momentum. 

It’s a great metaphor for marketing. Because that momentum isn’t the product of any single push. Instead, the energy is cumulative, generated by a lot of little pushes, with the whole greater than the sum of its parts.

Ideally, marketing and sales should work the same way. The energy, leads, and revenue created by marketing efforts is not due to any single channel, piece of content, or campaign; it’s a cumulative effect. And once it really gets going, a good marketing campaign keeps spinning. It generates energy.

Putting the customer at the center

Instead of a funnel into which prospective customers are unceremoniously dumped, the flywheel puts the customer at the center of the wheel: the axle.

Hubspot CEO Brian Halligan, for example, sees the customer as the lynchpin, with the flywheel itself divided into three equal segments, each representing stages along the customer journey: attract, engage, and delight. Each area creates energy and passes it along to the next, with the delight phase feeding back into attract.

Other flywheel devotees divide the disc into Marketing, Sales, and Service — again putting the customer in the center position. Each effort feeds into the next, cycling around and around, but always circling the customer.

This may be the most important aspect of the flywheel model — that it centers the customer. The funnel, on the other hand, doesn’t consider how those customers can feed back into the funnel (or the flywheel) to help create additional growth and engagement.

The funnel can’t conceive of customers buying from you more than once, so the momentum you build acquiring customers via the funnel just falls away. Following every quarter, every customer, every conversion — you’re starting all over again.

Learning to fly

The momentum of a flywheel is determined by three primary pieces:

  1. The weight of the wheel

With a physical flywheel, the greater the mass of the flywheel, the greater its momentum and the harder it is to stop. In the customer-focused model, the “weight” looks like an exceptional customer service experience that builds your reputation and brand in ways that create retention, build ambassadors, and deliver value into your marketing and sales segments. The way that you deliver that customer experience will be unique to your business model.

  1. How fast you spin it

The speed in the flywheel model is really about the number of “pushes” you give the wheel. How much content is your marketing team delivering? Which channels are you using to reach prospects? How many leads are coming from the content?

  1. The friction

Reducing flywheel friction is about ensuring customers remain satisfied and keeping your efforts aligned. If poor sales performance is slowing the momentum from marketing — or if poor service is hurting retention of hard-won sales — your flywheel will slow down, and your business will suffer. On the other hand, when everything is aligned, your efforts will feed into each other and keep your flywheel humming along.

Finding alignment and purpose

It’s one thing to draw up a model and another to align cross-organizational efforts in real life. Part of finding alignment is cultural, getting leadership to buy in and coordinating communication among departments. But a huge part of the lift has to be operational — and will be dependent on having technology that enables marketing, sales, and service to coordinate.

At CallTrackingMetrics (CTM), we’ve been thinking this way for some time now — though we only recently discovered the flywheel model. Our call intelligence and management platform brings together all the three segments of the flywheel: marketing, sales, and service.

It tracks call sources, lets agents tag and score calls, helps businesses respond immediately to inquiries, and provides a data-rich environment that can inform stakeholders across organizations about marketing, sales, and service performance. It also helps create reporting to determine returns on investment for content and campaigns, customer feedback, and more. In short, it makes it easier to understand and engage with customers in a meaningful, helpful way.

That engagement matters. A lot. Because, at the end of the day, marketing and sales are all about creating better experiences along your customers’ journeys. And the funnel model has never recognized the important part customer service teams play in generating customer retention, brand building, and developing stronger relationships and alignment between your business and your customers — as well as within the disparate teams in your organization.

In the end, the flywheel ensures that everyone in your business shares the same purpose: keeping the flywheel spinning, in order to create better relationships with and experiences for your customers. However hard it might seem to get it spinning at first, once the flywheel gains momentum and sales start churning, it’s well worth the effort.

The post From funnel to flywheel appeared first on Marketing Land.

The Practical Guide to Analyzing and Optimizing Your Blog

Google Analytics can be an intimidating tool to many marketers. It contains tons of information about your website visitors, but unlocking insights and coming up with action items is often a challenge when you’re faced with so much data. To avoid…

Crazy Egg's Practical Guide To Analyzing A Webpage

Google Analytics can be an intimidating tool to many marketers. It contains tons of information about your website visitors, but unlocking insights and coming up with action items is often a challenge when you’re faced with so much data. To avoid data paralysis, we recommend using Google Analytics to uncover your most popular webpages (let’s say your Top 5 to begin with), and then using Crazy Egg’s user behavior reports (Heatmaps, Scrollmaps, Confetti, Overlay and List) and A/B testing tools to optimize them. That way, every positive design change you make has the biggest impact to a visitor’s experience of...

The post The Practical Guide to Analyzing and Optimizing Your Blog appeared first on The Daily Egg.

The Expert’s Guide to A/B Testing During the Holiday Season

In 2016, online spending topped in-store shopping for the first time ever. That trend continued in 2017, with Adobe Digital Insights reporting that 2017 holiday sales surpassed $91.7 billion, marking 11% YoY growth. Peak season offers peak opportunities for experimentation programs. Increased traffic and conversion rates open the door for higher velocity, shorter durations, and lower minimum […]

The post The Expert’s Guide to A/B Testing During the Holiday Season appeared first on Brooks Bell.

In 2016, online spending topped in-store shopping for the first time ever. That trend continued in 2017, with Adobe Digital Insights reporting that 2017 holiday sales surpassed $91.7 billion, marking 11% YoY growth.

Peak season offers peak opportunities for experimentation programs. Increased traffic and conversion rates open the door for higher velocity, shorter durations, and lower minimum detectable lifts without compromising statistical significance.

If you haven’t already created your experimentation strategy, the time is now. But here are some essential factors to consider while creating your holiday testing game plan.

Maximize Your Holiday Window
Thanksgiving Day kicks off the peak holiday season, which continues through December 23. If you know your holiday window and website traffic patterns and expectations, you’ve got what it takes to take full advantage of this opportunity.

It can get complicated, but here’s a simple way to start:

  1. Define your holiday window. Consult past data to determine when traffic and conversion increases start and stop.
  2. Layer in the changes your organization is forecasting over last year. For example, one of our clients is expecting a five percent increase in traffic over last year’s holiday season. That intel is reflected in our traffic assumptions.
  3. Start your roadmap with the most valuable pages so that early wins can positively impact the rest of the holiday season. Create a punch list of pages with this in mind.
  4. Use traffic assumptions, desired statistical significance, and minimum detectable lift to determine the sample size and duration of tests.
  5. Continue this process to fill the window of time. Use these dates to mobilize your team, communicating key dates of test strategy kickoff, when tests will move into development, when they will launch and end and when results will be shared.

Communication is Critical
Since the holiday season represents a large portion of annual revenue, stress and emotions run high. As a result, it’s important to create your communication plan in advance. Determine who your stakeholders are, the optimal frequency of updates and what information needs to be shared. This isn’t the time for surprises or big reveals, so plan to devote a chunk of time to telling the story of your program and communicating its value.

The Weather Outside May Not Be the Only Freeze You’re Experiencing

Some organizations implement a freeze on development code updates and changes during the holiday season to avoid the risk of broken digital experiences or performance disruptions.  Get acclimated with your company’s approach so you can have a plan for implementing winning test programs.

The ideal scenario is to push winners immediately into production. Based on years of experience with enterprise clients, Brooks Bell strongly advocates this approach so you can maximize the impact of that winning test.

If production updates aren’t on the table because of a code freeze, don’t immediately jump to the decision to push the winner to 100 percent through your testing tool. Though it sounds like the best way to manage through code freezes, it could cause delays and create an undesirable experience. Before you make the decision how to handle, get your organization’s development experts involved to help you evaluate the risks and rewards.

Holiday Shoppers are Different
Think about your own shopping behaviors during the holidays compared to the rest of the year.

When I’m shopping during the holidays, I find myself on a mission to knock out my shopping list. As the countdown clock ticks away in my brain (and often literally on websites), I have a very real and intense sense of urgency. For me, customer confidence indicators, obvious savings and a clear and easy path to checkout are the ticket.

During the rest of the year, shopping is more leisurely for me and allows time for more browsing and consideration. I may even visit a website a few times before making a purchase. I zoom in on product details. I read customer reviews. I have more time, and the only restrictions are my own.

I’m the same person but have a very different mindset. The same goes for your customers. Keep this in mind as you develop your holiday testing roadmap.

Here are four tips to help ensure your holiday experimentation wins continue to add business value:

  • Keep it simple. As illustrated in my example above, successful holiday strategies are frequently based on a streamlined path to purchase, removing any friction and creating a sense of urgency and scarcity.
  • Test your hypotheses again after the holiday season. Do these experiences still produce a conversion lift when the holiday rush isn’t in full effect? If not, it’s okay! It’s an important learning you can use to build your Holiday/Non-Holiday playbook to make each holiday season better than the last.
  • Know your “Out of Stock” strategy. Regardless of what changes you make to your Product Detail page, nothing zaps excitement out of a customer experience faster than something being Out of Stock. Understand how your site handles Out of Stock messages, such as using red copy or suggesting alternate options. If it’s less than optimal, do some early testing to determine the most effective messaging. If your site includes a lot of Out of Stock product, it’s even more important to make sure it‘s been optimized.
  • Document your findings. Carve out time to tell the story of your testing through the chaos of increased velocity. The data and insights will be helpful after the rush and can greatly influence your future program success. Be sure to look at new, returning and loyal segments, and evaluate the differences in their holiday and non-holiday shopping behaviors.

For more intel on how to make the most of the merry months ahead, download our white paper, “5 Testing Tips for the Holidays.”

Need help developing a game plan for holiday testing? Contact us today!

The post The Expert’s Guide to A/B Testing During the Holiday Season appeared first on Brooks Bell.

Bring order to chaos: Wrangling data for actionable insights

How to bring an overwhelming amount of data under control and use the insights gained throughout your business.

The post Bring order to chaos: Wrangling data for actionable insights appeared first on Marketing Land.

Producing actionable insights is one of the most challenging issues that brands face today. Urgency is ever-present, pushing marketers and analysts to rush decisions. But urgency is only half of the problem. Making the situation more chaotic is the fact that we are simultaneously awash in waves of data from too many sources. Between the urgency to produce results combined with the massive sea of data, we are inundated us every time we wade in and then simply washed back to shore.

So where do we start? Transactional, engagement, or demographic data? Prospecting or retention? The inundation keeps pushing us back.

There are strategies to navigate the churn and turbidity, and remedy those issues. Sometimes we simply need to take a step back, narrow our focus, and even get a little ruthless.

Insights begin with goal-setting

First, we need leadership teams to get ruthless with what really matters. Analytics can’t chase the shiny object or rely on some utopian commerce breakthrough — if only we could find attribution in some rabbit-hole metric.

Think bigger. Get brutal with company and divisional goals.

Great goals have a couple of key characteristics in common. First, they’re specific — they have clear expectations and a path forward to measure and show success. Great goals also unify teams instead of dispersing them in different directions where everyone has a separate idea of how they can accomplish them.

To reach goals, every single person needs to be pulling the boat in the same direction. Great goals produce unity, which in turn helps to focus analytical firepower where it matters most. Remove the rest.

Where to start

The lowest hanging fruit is almost always customer retention. It’s the easiest behavior to shift; it has the most room to grow; it’s the most profitable. One way to understand the importance of retention is to ask this question: if a brand acquires a new customer, what does that matter if that brand can’t keep the customer engaged? Prospecting without first nailing down the current customer makes teams spin their wheels and waste energy.

Align your performance indicators

So, we have our goals narrowed down and all teams are working towards a common purpose.  The next step is to flawlessly align our performance indicators to those stringently selected goals. Again, narrow your focus and be strict with the fidelity of indicators to goals.  They should have either a clear cause-and-effect relationship or a very strong correlation to prove success.

Once we’ve identified those core components, we can simply let the rest of the data wash away.  It takes work up front, but that work will be rewarded with a strong path forward and will avoid data paralysis down the road. By deriving indicators naturally from a core set of goals, you organically narrow the data set, so we can focus on producing insights that drive change.

It’s easy to see how many brands can get stuck in the mud during this phase. There are so many temptations, so many paths to take that could work if only for one added piece that we don’t have in the model. But this is a faulty mindset and the effort will be wasted with little to show for all that added work. Put the blinders on and be strict.

Where to start

The answer is almost always transactional data, especially if we’ve felt the impact of overwhelming data paralysis. Stick to transactional indicators early. They’re reliable and strongly aligned to behavior. What shows customer sentiment better: a Facebook Like or purchasing items?

Measure, rinse, repeat

Lastly, all of that work is useless if we don’t have a measurement plan in place to prove success. If we can’t measure, it doesn’t matter.

The best approach is a rigorous test-and-learn strategy. Not only does it prove success, but it also provides actionable insights for the future to help build individual successes into larger groups of changes across channels and teams to drive and achieve goals.

Analytics teams can definitely get backed up, especially with A/B testing. Sometimes the waitlist is daunting. But there are two good options if that happens. First, consider an outside agency dedicated to helping us learn about the customer. An outside source can provide focus when things get too tight for internal teams to produce results.

The other option is to test historically. I can hear the gasps and guffaws of analytics teams, but we need to read the tea leaves however we can to produce results. That means pushing changes to market and measuring year-over-year data instead of one-off direct causations.  That option is better suited to areas where we already know best practices or have some data points to suggest the right decisions with high degrees of confidence.

Another reason it’s a viable option — and why analysts should love it — is that it frees up the testing schedule dramatically. So many tests don’t really need to be run in an A/B format; sometimes we have years of historical data or mountains of best-practice to influence our decision. In those instances, measurement is less of a read and more of a confirmation.

Bring order to chaos

These ideas may sound simple and, to a large degree, they are simple. They’re foundational. But without a foundation, how can we achieve our brand aspirations?

So many brands run before they can walk and they fall flat. To bring order to chaos, we need to start with the lowest common denominators to build on our learnings. Start small, grow big. Incrementally and soon, teams from every channel will have the learnings they need to act and provide the best experiences possible for both the brands and the customers.

The post Bring order to chaos: Wrangling data for actionable insights appeared first on Marketing Land.

Google Data Studio comes out of beta

The company continues to develop new features for the reporting product.

The post Google Data Studio comes out of beta appeared first on Marketing Land.

Google’s two-year-old free reporting and data visualization platform, Google Data Studio, is now generally available.

Integrations and data connectors. Data Studio, now part of Google Marketing Platform, has native integrations with Google Analytics, Google Ads, Display & Video 360, Search Ads 360, YouTube Analytics, Google Sheets and Google BigQuery. Marketers can also connect to hundreds of other non-Google data sources.

A crop of data connectors from companies like Supermetrics, a digital analytics and reporting tool provider, has also sprouted to help marketers pull data from multiple sources into Data Studio.

More new features. Over the past two years, Google has steadily added features and capabilities to Data Studio. As of this month, Google Marketing Platform (GMP) users can access Data Studio reports in other GMP products, including Analytics, Optimize and Tag Manager. Among other updates, in August, Google added the ability to combine data from multiple sources in a single chart or table with data blending (shown above).

Google says millions now use the product.

The post Google Data Studio comes out of beta appeared first on Marketing Land.

How to supercharge the Salesforce lead source field

Strategic management of the lead source field within Salesforce setup will unlock the magic of campaign tracking and measure the efforts of your paid media and content efforts. Here’s how.

The post How to supercharge the Salesforce lead source field appeared first on Marketing Land.

Salesforce lead source has long been the data point that has ruled measurement of marketing initiatives. This field tracks channel attribution and is used to measure return on marketing investments.

However, in today’s marketplace, the field is very limited out of the box. Absent multitouch attribution flexibility, you really only get one lead source on a record within the database. But what about second, third and fourth touches?

There are a few options utilizing just lead source on its own, but they all have limitations:

  1. We can ignore all touches after the first and stick to the original source only. This is often the method we see used at most companies, and it leads to inaccurate data
  2. The second option is to override the existing lead source with each new touch. This leaves you with the most recent lead source only. Unfortunately, this destroys info and creates inaccurate data, leading to really scary decision-making.
  3. The last option is to create a new lead record for each touch. This approach is the most disruptive, leading to mass confusion and degraded data quality.

So, how do we measure the big picture of a combination of channel influence and maintain the integrity of the database? The answer is to use campaign tracking alongside a customized lead source architecture.

In this post, we’ll focus on how to get your lead source field customized with a level of granularity that serves the business while maintaining the integrity of the data.

Lead source field review

Out of the box, the default lead source list in Salesforce is not granular enough. This list predates most of the channels we utilize in marketing today — rolling all digital channel activity into one bucket labeled “web.”

Neglecting to customize this list during a Salesforce implementation leads to pandemonium and frustration once data begins to populate the reports, and marketing can’t see the results of their efforts clearly enough. Which then leads to shooting in the dark and misalignment between sales and marketing.

We highly recommend you perform an audit of your lead source field options and customize them for your organization. Get rid of lead sources that don’t serve you and add lead sources you would like to track. This can easily be done with a simple spreadsheet to allow everyone to come together and agree on what level of granularity you would like to see.

Customize Salesforce lead source

Once you have gone through your existing lead source list and pruned the lead sources that don’t belong, you can draft the new lead sources that should be added. Now, it’s time to go through and look for missing granularity and opportunity to consolidate.

Effective marketers and data folks always want things tracked as granularly as possible. This often leads to a new lead source for every single activity, event and campaign, which creates a bloated database and makes for difficult reporting.

You’ll likely find that you have several lead sources that can be combined or eliminated. Look for opportunities to standardize your lead sources similar to Google Analytics parameters. If you need additional details, add more fields.

Standardize data entry

Once things are cleaned up, we highly recommend you standardize and automate your data entry. The lead source field should be locked down and set automatically by the system, not by human hands. You can do this using a web-to-lead form (first touch email acquisition) or by passing data from your marketing automation tool (first touch visit).

Once the data is set, don’t allow it to change or allow it to map to other objects.

Strategic management of the lead source field within your Salesforce setup will allow you to unlock the magic of campaign tracking and really measure the efforts of your paid media campaigns and content efforts.

The post How to supercharge the Salesforce lead source field appeared first on Marketing Land.

Who’s Hiring in September?

Pumpkin spice is not the only thing in surplus this month, take a look at some job postings around experimentation and personalization. Here are our picks: Director, Digital Strategy – Universal Orlando is looking for a Director to “champion the consumer’s journey across channels to achieve business and campaign objectives and collaborates with leaders of […]

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


Pumpkin spice is not the only thing in surplus this month, take a look at some job postings around experimentation and personalization.

Here are our picks:

Director, Digital Strategy – Universal Orlando is looking for a Director to “champion the consumer’s journey across channels to achieve business and campaign objectives and collaborates with leaders of non-digital channels to ideate and recommend campaign integration opportunities.”

Senior Web Experimentation Lead – The marketing experimentation team at esurance is looking for a leader to “embed an experimentation culture into the esurance DNA in San Francisco. This role will deliver increased cost savings, additional revenue and industry leading user experiences through the power of site testing technology and the scientific rigor of controlled experimentation.”

Senior User Experience & Small Business Project Manager –  Lenovo is seeking a candidate in Raleigh, NC to drive “UX projects to improve the online customer experience for Lenovo.com globally. The project manager will manage the identification, conception, definition, design, testing and implementation of UX projects with the goal of improving the customer experience, online engagement and purchase conversion.”

Manager of Digital Testing & Optimization, Analytics – Join the digital analytics and optimization team at L Brands in Reynoldsburg, Ohio and “lead digital testing and optimization efforts. This person will champion the advancement of testing and optimization capabilities and be viewed as the optimization evangelist for different brand partners.”

Digital Marketing Manager, Personalization – looking for an ambitious learner to lead a test & learn strategy through experimentation for our digital marketing channels. You will be the leader and subject matter expert of A/B testing with the goal of developing the strategy and approach on personalization.

E-Commerce & Digital Operations Manager – In New York, Zacharys Fine Wine is looking for a candidate to plan and execute “digital and website activities for retail including: content, merchandising, landing pages, site search, product recommendations, personalization, loyalty and other on-site conversion optimization tools.”

Sr. Integrated Marketing Manager – Web Analyst – Microsoft in Redmond, Washington is looking to fill a role to “work with the web lead to strategize, create, manage, execute and optimize web analytics. This includes building experimentation and personalization programs for Dynamics 365 and Power BI.”

Director, eCommerce – “Drive the strategy, development, implementation, and continued improvement of the eCommerce booking experience for Carnival Cruise Line” in Miami, Florida.  “Help lead the presentation across the eCommerce website and mobile app, supporting the integrated programs, promotions and initiatives across the organization.”

Sr Analyst A/B Testing & Site Optimization – Help “drive and support A/B and multivariate testing initiatives on the Homedepot.com site” in Atlanta, Georgia. “The Sr Analyst will be responsible for statistical design, analysis, and reporting aimed at the continued improvement of Homedepot.com onsite experience, with a focus on partnership for making data-driven decisions that drive improved conversion.”

User Experience (UX) Designer – Join the Brooks Bell’s UX team in Raleigh, North Carolina.  “The core function of this role is to research, concept, design, user test, and produce all files needed to execute A/B tests for our clients. This includes creating digital assets that are consistent with the development team’s standards and templates, as well as selecting images, designing layouts, and creating digital experiences that answer user issues outlined by our digital analytics and user research sessions.”

Trying to fill a position in testing and optimization? Send us your posting and we’ll include it on our next post!

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

How to capitalize on the competitive advantage of real-time data analysis

Contributor Stela Yordanova explains how to capitalize on the competitive advantage provided by real-time data analysis.

The post How to capitalize on the competitive advantage of real-time data analysis appeared first on Marketing Land.

The Real-Time report in Google Analytics allows you to monitor website activity as it actually occurs on your website or app. The report is continuously updated, and website activity is reported just a few seconds after it happens. This immediacy of real-time data provides digital marketers with unique and valuable insights.

There are many ways you can use real-time reporting such as gauging the effectiveness of your mobile app through event tracking and monitoring one-day promotions on your site.  Today I want to focus on and recommend marketers use Google’s Real-Time report for three specific things:

  1. To quickly monitor results for short-term campaigns or promotional efforts.
  2. To track immediate interaction with newly published content.
  3. To test and verify Google Analytics and Google Tag Manager implementation.

Real-Time Overview

The Real-Time report contains an Overview plus five specific reports:

  • Location report.
  • Traffic Sources report.
  • Content report.
  • Events report.
  • Conversion report.

Each report is described below with suggestions on how marketers should use them to analyze real-time website data and improve marketing results.

 

[Read the full article on Search Engine Land.]

The post How to capitalize on the competitive advantage of real-time data analysis appeared first on Marketing Land.

Who’s Hiring in August?

Here are our picks: Director, Digital Marketing, Estee Lauder – North America – “Develop, execute and manage best in class national and coop digital marketing programs to promote brand awareness and drive retail sales” in New York.  “Manage digital budget, timelines and drive creative production for asset development.” VP, Digital Technology – Total Wine & More […]

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

Here are our picks:

Director, Digital Marketing, Estee Lauder – North America – “Develop, execute and manage best in class national and coop digital marketing programs to promote brand awareness and drive retail sales” in New York.  “Manage digital budget, timelines and drive creative production for asset development.”

VP, Digital Technology – Total Wine & More is looking for a candidate in Raleigh, North Carolina to “build the right technology strategy to support the Omni-channel efforts across the company.  This individual should have deep experience with high-traffic, content-rich retail websites sites and applications focused on bringing digital solutions to all store and customer interactions.”

Associate Director, Testing (Marketing Analytics) – “Help the World’s largest omnichannel retailer, Walmart eCommerce, drive optimal efficiency and effectiveness of our Marketing investment through continuous testing of optimization scenarios” in San Bruno.

Personalization & Site Testing Analyst – Levi Strauss & Company is looking for a candidate in San Francisco to “play a key role in accelerating the growth of Levi’s and Dockers eCommerce businesses via site testing & personalization.”

UX/UI Developer & Designer – Direct energy is looking for a “passionate and dynamic Mobile UX/UI Design & Develop professional who understands the intricacies of cross-browser development and knows how to build simple interfaces by writing maintainable CSS.”

Digital Marketing Manager, Personalization – Charlotte Russe is going through an “exciting digital transformation to become a best-in-class fast-fashion retailer.” They are looking for an “ambitious learner to lead a test and learn strategy through experimentation for their digital marketing channels” in San Francisco.

Senior Digital Optimization & Testing Analyst – Dignity Health is searching for a candidate in San Francisco to “improve the user experience through Personalization, A/B & Multivariate testing and inform experimentation strategy across the organization.”

Testing & Personalization Specialist, Analytics & Data – In New York, IBM is seeking a “champion of user-centric thinking to help shape marketing through A/B testing and personalization.”

Manager, Site Analytics and Optimization – “Manage the optimization of Eddie Bauer’s digital properties and support a testing and analysis-based culture to drive customer experience” and business goals in Bellevue, Washington.

Vice President, Finance – Brooks Bell is looking for someone to join the leadership team in Raleigh, North Carolina.  They will be responsible for financial strategy, accounting and contract negotiations with clients.

Help us, help you! Trying to fill a position in testing and optimization? Send us your posting and we’ll include it on our next post!

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

Adobe is Killing Ad Hoc Analysis & Everything is Going To Be Fine

Where were you when you heard the news? I was checking my analytics team’s Slack channel at work when my teammate shared this screenshot: At first, my thoughts went to Java. Then, it really hit me. Ad Hoc?! No. That’s not possible. But instead of letting this news ruin my week, I thought to channel […]

The post Adobe is Killing Ad Hoc Analysis & Everything is Going To Be Fine appeared first on Brooks Bell.

Where were you when you heard the news? I was checking my analytics team’s Slack channel at work when my teammate shared this screenshot:

At first, my thoughts went to Java. Then, it really hit me.

Ad Hoc?!

No.

That’s not possible.

But instead of letting this news ruin my week, I thought to channel my mom’s advice from my junior high school days: “Don’t get upset about things that are outside of your control.”

If I could influence Adobe, I would definitely try.  Actually, is anyone at Adobe reading this? Is there any chance that you could reverse the decision? No? Ok, that’s fine, too.

So, deep breaths. I’m going to jot down why this gave me feelings and try to determine whether my perceived issues are real problems at all. And, I thought, why not bring you all along for this personal therapy session of mine?

 

First, let’s unpack why this is such a big deal.

If you’re unfamiliar, Ad Hoc Analysis is a tool within Adobe Analytics. It’s used by analysts, like myself, to analyze and report on website performance— engagement, conversions, eCommerce, etc.

Adobe has another reporting and analysis tool within Analytics, Analysis Workspace. It operates in a similar fashion to Ad Hoc, but in a more visual way. The company is already encouraging Ad Hoc users to make the switch over to Workspace. 

Ad Hoc Analysis

Analysis Workspace

Rather than using the reporting dashboards available within various testing platforms, most analysts connect their test results to analytics tools like Adobe Analytics or Google Analytics.

Using these more sophisticated tools enables us to view A/B test results in conjunction with any one of the dimensions, segments, time periods, or metrics that exist within the analytics tools. 

So if Workspace exists, you’re probably wondering why we’re still stuck on Ad Hoc over here. 

First, Ad Hoc is flexible.  Once you’ve learned the capabilities, and assuming your site has the proper tagging in place, Ad Hoc enables you to answer any business question; business questions cause our little analyst gears to turn and assembling a report, custom segments, or calculated metrics transforms into a neat little puzzle to solve.

Also, analysts are creatures of habit.  When it comes to doing our jobs, analysts like to stick with what we know. Solving problems or answering questions is enough of a challenge, and we don’t want to spend extra time thinking about where to find segments or buttons in a tool. Those of us who live in Ad Hoc on a regular basis will need a little time to adjust. Bear with us.

The impact of this on my own day-to-day wasn’t lost on me. So, even as I mourned the loss of Ad Hoc, I also began to consider the challenges ahead.

Here were my concerns about switching from Ad Hoc to Workspace

Can I create all of my complex segments and calculated metrics in Workspace? Even though the two products look different, the functionality seems to be all there.  In general, Workspace is a prettier product; Ad Hoc just feels more real. And let’s face it: when things look a little too pretty, analysts become skeptical.

Doesn’t Workspace have limits on the number of rows you can export? Yes. Today, Workspace only enables you to view and export up to 400 rows at a time (though the default view is 50). So, while this isn’t something that we can work with today, Adobe does have plans to increase downloads for up to 50,000 rows from a freeform table. Cue: huge sigh of relief.


Should I use Data Warehouse instead? 
Adobe Analytics’ Data Warehouse tool is better for setting up a large and/or scheduled data-pulls. It’s not a good option for an exploratory tool.

Isn’t Workspace buggy and slow? When I asked my colleagues what they thought about Workspace, many of them used the word “clunky.” This impression exists because Workspace is a browser-based tool. It also automatically reloads your report every. single. time. you make a change. Compare this to AdHoc, where you can change as many elements as you want, but the report will only refresh when you hit that magical little “Replace Table” button.

Maybe this is in the list of upcoming upgrades, but I haven’t come across any mention of it yet.

How will I explore my data?
Short answer: Differently.

Long answer: Neither Workspace nor Data Warehouse are ideal for exploring new datasets. If you’re already completely up-to-speed with your dataset’s tagging, metrics props and eVars, you’re fine. However, when you get into new datasets, data exploration is critical to ensure that you are getting the most out of your data and analysis. This will be a bigger challenge for agencies and consultancies (like Brooks Bell), as data exploration is key to kicking off our work with new clients.

Workspace isn’t a bad option. It’s just different.

While there are definitely redundancies between Workspace and Ad Hoc, there are actually quite a few benefits to switching to Workspace.

First, Workspace is good for on-going test reporting.  Here at Brooks Bell, we can set up and share dashboards with both our colleagues and our clients, enabling everyone to actively monitor test results. This is particularly nice at the beginning of a test’s lifecycle and allows for transparency throughout the entire process.

It also has an undo option.  Many Ad Hoc power users can relate to the combination of defeat and hope they feel after accidentally closing the wrong tab, attempting that “close without saving” trick, while praying they didn’t change too much since last save.

Finally, any changes you make to segments will automatically update in Workspace. Meanwhile, in Ad Hoc, you have to remove your segment from the work area, and then add it back in from the full list of segments. Fewer steps = less time.

Finally, how to prepare for a world without Ad Hoc

1. Start your transition today.  I opened up Workspace for the first time in a while just last week.  I’m now using it to do most of what I would normally do in Ad Hoc. So long as I don’t update Java, I know I can always fall back on Ad Hoc for the large data-pulls and data exploration until those features are in place in Workspace.  For now, though, it’s all about building new “muscle memory” as I incorporate Workspace in my workflow.

2. Check out this process documentation for making the transition. I read through this a few days after hearing the news and wish I had read it sooner.

3. If you plan to continue to use Ad Hoc for the time being, don’t update Java. Ad Hoc will no longer work with future Java updates.

4. Give feedback!  Adobe is soliciting feedback all over the place right now! This shows that they care about their users and want Workspace to be a useful tool. Don’t hold back on feature requests—it never hurts to ask.

Ultimately, we all had a sense this day would come, especially as data and analytics technologies continue to develop. I feel much better now that I’ve dove into this change headfirst—I hope you do too!

The post Adobe is Killing Ad Hoc Analysis & Everything is Going To Be Fine appeared first on Brooks Bell.