Category: Webinars and Talks

WEBINAR: A Programmatic Buyer’s Look at the ISBA Report’s “Unknown Delta”

A Programmatic Buyer’s Look at the “Unknown Delta”

Recently the Incorporated Society of British Advertisers (ISBA) set out to shine a light on the programmatic advertising supply chain, but despite exhaustive efforts to map and attribute every advertising dollar, the subsequent report could not account for a sizable fraction of digital advertising budgets. This “unknown delta,” as the ISBA calls it, is associated with causes ranging from fraud to inventory reselling. But regardless of the reasons, the ISBA report exposes a complex system that lacks transparency.

“[The unknown delta] is not meant to be assumed as fraud….This is important for anyone who is thoughtfully assessing this study; the unknowns can ideally become knowns.”

– Rachel Adams, Head of Media Activation US, MightyHive

The ISBA report is the focus of the latest episode of Live with MightyHive and features Rachel Adams, Head of Media Activation, MightyHive US. Adams brings years of agency buying experience and countless hours working with MightyHive clients on in-housing strategies and implementation. Together with Senior Director of Marketing Myles Younger, the two cover some of the report’s findings and strategies for optimizing the digital advertising supply chain and improving transparency.

This episode of “Live with MightyHive covers: 

  • Findings from the ISBA report
  • The advantages of simplifying your supply chain
  • The increasingly important role of transparency

Get the Video

Watch Episode 3: A Programmatic Buyer’s Look at the ISBA Report’s “Unknown Delta”, and view the slides below.

Subscribe to Live with MightyHive to hear about all of our upcoming webinar-workshops. And if there’s a topic you’re interested in, email us at live@mightyhive.com.

And check out MightyHive CEO Pete Kim’s thoughts on the ISBA report here: Marketers Deserve Better.

Identifying Significance in Your Analytics Data

 
A few weeks ago I had the chance to help launch our new “Live with MightyHive” series. My colleague Myles Younger and I chatted about how to distill significance and causality from analytics data, and then how to act on those types of insights. You can watch the full episode and access the slide deck below.

If you want to chat further with MightyHive about advanced analytics solutions like these, please reach out to us at questions@mightyhive.com.

What is significance?

Making decisions based on data needs the support of a robust measure of confidence in the data.

Off the back of an event of some sort (campaign starts, new app feature, global pandemic), if we observe any change in our data we need to be confident the “thing” that happened was actually responsible for the change in data—not just a correlation. We need to be able to demonstrate that had this thing not happened, the data wouldn’t have changed.

Then we can infer a causal relationship between the event and the change in the data. Remember—it’s still a probability, we can never prove causality in a categorical sense, but we can be highly confident (and it’s way better than guessing!). We can remove emotion and unconscious bias from decision-making. We don’t eyeball data or use our gut—mathematics informs the decision making process.

Here’s the full chat and slides from last week’s “Live with MightyHive” episode (scroll to the end for the slides):

How does it work?

The technology behind the Google CausalImpact R package that was demonstrated in the episode constructs a Bayesian structural time-series model and then tries to predict the counterfactual.

Simply, the mathematical model uses data prior to the event to predict what the data would look like had the event not happened. Important: the prediction is actually a probabilistic range of values. If the historic data is noisy, then the accuracy of the prediction will change. See the screenshot below from the demo walk through linked above. In the image below, the blue shaded area is the prediction (synthetic control estimator) from the model. If the observed data falls outside the blue region, we have significance!

The blue region gets bigger with noisier data. The broader the blue region, the more extreme the observation will need to be in order to achieve a significant signal.

Using Google CausalImpact

You can use the CausalImpact package with as little as three lines of R. R Studio is open source or you could try it out using rstudio.cloud.

Be advised, if you install the CausalImpact package locally, due to dependencies, you’ll need at least v3.5 of R. I updated Linux on the Chromebook to get the latest version of R and R Studio via this very useful article and the package installation was very straightforward.

There’s another option thanks to Mark Edmondson from IIH Nordic. Mark wrote a great Shiny app front end for CausalImpact that’s free to use, so you can explore significance in your own GA data.

Using significance to establish causality and take action

We used the package to analyse client data to confidently answer key business questions that arose regarding KPI changes since the UK was locked down.

As well as considering YTD data (setting the ‘event’ as Jan 1), we use pre- and post-lockdown (Mar 9) date periods. Data shows clear patterns in purchase behaviour for retails sites. Media sites appear to exhibit explosive growth. However, the specifics regarding growth areas of content are highly informative—not what you’d expect to see by just eyeballing the data from afar.

For retail and media clients, the ability to identify current and future growth areas with confidence is a highly valuable tactic. At a strategic level, the forecast output from CausalImpact is highly actionable in driving campaign content, budgets, and timing.

While tactics for the current global situation include “managing,” there is a clear near for preparation as well. Making decisions on current data and using forecasts with confidence proves to be valuable for our clients.

Additional Resources

Thank you for reading! The slides from the episode can be accessed here:
 

Watch the CausalImpact R package introductory video here (mandatory viewing!):
youtube.com/watch?v=GTgZfCltMm8

Remember to sign up here for future Live with MightyHive episodes:
livewithmightyhive.splashthat.com

Introducing: Live with MightyHive

 

MightyHive is launching a new series of webinar-workshops, Live with MightyHive, to give you quick, actionable insights from MightyHive subject matter experts and partners. In each workshop, we spotlight one aspect of digital marketing, such as data analytics, performance, attribution, privacy, and more. We interview specialists with years of field experience to draw out useful tactics that can be applied today and then we welcome questions from our live audience.

We kicked off our first episode with Doug Hall, MightyHive Senior Director of Analytics EMEA, who joined Live with MightyHive to discuss using Google CausalImpact to extract significance and causality from Google Analytics data. Hall also shared techniques for presenting data significance in ways that tell the story and enable action.

Because we are dealing with probabilities…the explanation needs to be absolutely clear. If you can explain the difference between significance and noise, then you can definitely start to use this tool. If you start to explain Bayesian time series, inference models and machine learning, then you are going to lose people real quickly.”

— Doug Hall, Senior Director of Analytics, EMEA

 

Subscribe to “Live with MightyHive” to stay informed about our upcoming webinars like “Data Quality Nightmares” with Julien Coquet, Director of Analytics, EMEA on Thursday, May 14.

And we want to hear from you! If there’s a topic you’re interested in, email us at live@mightyhive.com.

 

 

WEBINAR: How performance marketers are boosting results with CPM buying

 

Performance marketers may be reluctant to invest in CPM-based campaigns, but avoiding top-of-funnel strategies presents a risk. By building awareness earlier in the sales cycle, competitors will drive more customers toward their PPC marketing tactics. Big advertisers with a history of leaning heavily on performance marketing like Topshop, Booking Holdings, Adidas and Old Navy have all openly discussed their plans to decrease reliance on performance ads and establish a more balanced approach.

“One of the benefits of CPM-based buying is you can learn so much about who your users are, what their demographic data is, and what other things they are interested in.”

— Ellen Perfect, Senior Account Manager, MightyHive

To help performance marketers build successful CPM strategies, MightyHive and Hanapin Marketing teamed up for a webinar about using programmatic branding campaigns to drive customers down the funnel. This free webinar is a great primer for advertisers and teams looking to expand into CPM-based buying using a DSP—for example, expanding from Google Ads into Google Display & Video 360.

This webinar takes a close look at:

  • How performance marketers can better leverage the audience-building and reach expansion capabilities of programmatic and CPM-based buying
  • How successful programmatic advertisers define and measure KPIs
  • How to optimize performance and meet goals in programmatic and CPM-based campaigns

MightyHive Senior Account Manager Ellen Perfect shares her experience developing performance-driven CPM strategies. John Williams, Senior Account Manager at Hanapin, brings his expertise in cross-channel marketing to show how metrics work across multiple digital platforms.


John Williams
Account Manager,
Hanapin

Ellen Perfect
Account Manager,
MightyHive

Watch on demand now



Download the Slide Deck and Video that Explain Data Clean Rooms

Meet Your New Best Friend: the Data Clean Room

Recently I had the privilege of delivering a packed session at AdExchanger’s Programmatic I/O in New York. The session, titled “Meet Your New Best Friend: the Data Clean Room,” quickly brought marketers up to speed on:

  • What data clean rooms are
  • How they work
  • How they’ll help bridge the gap between user privacy and marketing insights

There was a lot of demand for the slides following the session! So we’ve packaged up the PowerPoint deck and the complete session video and made them available for download. Marketers, media buyers, and tech platforms are all looking for practical solutions to preserve measurement and insights in a privacy-first era. This deck offers an overview of data clean rooms that are available now (e.g., Ads Data Hub) as well as what might be coming next.

PREVIEW THE SLIDES


A few sample slides from “Meet Your New Best Friend: the Data Clean Room.”

Get up to speed on data clean rooms in under 30 minutes

Here’s a highlights reel of what the session covers in about 25 minutes and 44 slides:

  • How data clean rooms maintain privacy by being a “Switzerland” for data
  • An overview of Google’s Ads Data Hub, the best-documented data clean room
  • A look at Amazon’s purported clean room solution
  • Why Facebook’s data clean room should be called the “Keyser Söze of ad tech”
  • What strategic partnerships like Target + Disney might have to do with data clean rooms

DOWNLOAD THE SLIDE DECK & VIDEO

WEBINAR: How Do Sophisticated Marketers Think About Measurement?

 

Recently, MightyHive and Google set out to answer some questions about sophisticated programmatic advertisers’ best practices:

  • How are they building new connections to customers?
  • What discoveries are emerging from data and analytics?
  • How are marketers pushing technology to do more?

To foster an exchange of ideas about today’s most sophisticated marketers, MightyHive and Google collaborated on How Do Sophisticated Marketers Think About Programmatic & Measurement Maturity? Chris Brook, Director of Client Solutions at MightyHive, co-hosted alongside the Google Marketing Platform Customer Success Team.

“First-party data isn’t a tool, it’s the toolkit.”

— Chris Brook, Director of Client Solutions, MightyHive

Chris focused on the KPIs top marketers are using to determine the lifetime value (LTV) of a customer. He shared that the best insights are derived from a wide variety of first-party data sources (CRM, POS systems, customer loyalty programs, etc.) combined with user-data that is generated by owned web properties. Chris also touched on important issues facing sophisticated marketers today, such as new privacy regulations and the benefits of dynamic ad serving.

The webinar concludes with a walkthrough of how personalized, dynamically-generated promotional content for the Netflix series “Narcos” was able to cut production costs by 40% and boosted clickthrough rate by 60%.

The Fusion of Creative, Media, and Technology

Watch “The Fusion of Creative, Media, and Technology” (page opens in a new window)

At AdExchanger’s Programmatic I/O in San Francisco, MightyHive CEO Pete Kim took the stage to discuss the need for advertisers to adopt a unitary approach to their creative, media, and tech. Advertisers who fail to do so risk missing crucial opportunities to hold meaningful conversations with today’s ultra-savvy consumer.

Got Creative?

Jeff Goodby, Co-Chairman and Partner, Goodby Silverstein & Partners, implied in a 2018 AdWeek Op-Ed that technology debases creativity in advertising. Goodby suggests that using data and tech to inform programmatic media buys amounts to nothing more than “targeting and tonnage,” eliminating good creative altogether. He asserts that this model produces an expensive and ineffective structure for advertisers, and an unpleasant experience for consumers.

In his Programmatic I/O talk, however, Pete paints a very different picture of how data and tech actually work together to elevate creative. In fact, Pete says, not only does this model yield more relevant, dynamic creative, but it does so at scale and in a constant optimization loop, so it always gets better. 

creative big idea

The Big Idea

While there has been an undeniable sea change in the industry leading to major digital disruption, one thing hasn’t changed: great advertising still requires “the big idea.” But the machinations behind producing and disseminating creative to consumers continues to evolve.

“We believe that technology doesn’t debase creativity; if used correctly, it elevates it. We are all really different people… that’s why personalization is necessary.”

– Pete Kim, CEO, MightyHive

In the past, technological limitations required advertisers to generate one message, and “broadly cast” it to all consumers. Now, it’s possible to personalize creative and target consumers based on their demographics, preferences, and other criteria. In addition, we’re able to create, test, and iterate upon these creatives in near real-time.

Personalization is the New Table Stakes

For the first time in history, consumers can watch, read, and listen to anything they want at any given time. This new on-demand, cross-screen culture has raised the bar for advertisers to meet the quality of the entertainment their content is interrupting. Unfortunately for advertisers, this expectation for perfection and relevance across all media means that consumer sentiment around advertising has never been lower–and a one size fits all approach is unacceptable.

creative many to many

The Battle of the Good Idea

On creative teams past, there was a “gladiatorial” fight to determine which big idea actually got produced and saw the light of day. That one idea then became the basis for a static, inflexible campaign lasting weeks, or even months (in some cases years!). Now, Pete says, marketers are no longer “locked into” one creative (e.g., one commercial, one print ad, one radio ad) that gets produced and is written in stone until the campaign’s end. Granular targeting and creative optimization capabilities give advertisers the iterative flexibility to deliver the right message to the right consumer, on an ongoing basis.

What’s Next?

Because this creative, data, and technology loop is relatively new, we are just at the beginning of recognizing its true power. According to Pete, the next change is a mindset shift to catch up to our newfound technological capabilities. In addition to learning how best to leverage dynamic creative optimization and programmatic tools, we need to adapt our mindsets to suit the new ways consumers interact with media. creative mindset

Better, Faster, Cheaper

In order for advertisers to get their story across in a way that resonates, it’s crucial to move away from giant, costly campaigns once or twice a year to a constant conversation model. Dynamic creative and programmatic technology allows advertisers to have not just one, but millions of simultaneous, personalized conversations in real time.

“If you are only updating your campaigns a few times a year, it’s like having a conversation with somebody who always says the wrong thing, and takes months before they respond to what you just said.”

– Pete Kim, CEO, MightyHive

Watch Pete Kim’s full “The Fusion of Creative, Media, and Technology” session for further insights about unleashing creativity at scale.  

Event: ANA In-House Agency Conference

The MightyHive team is thrilled to be attending the sold out ANA In-House Agency Conference. MightyHive CEO Pete Kim will be joined by Josh Palau, VP Media Strategy and Platforms at Bayer to deliver a pre-conference session on Paving the Path to In-Housing Success.

Other speakers from PwC, Nationwide, Verizon, Clorox, GlaxoSmithKline, Bank of America, and more will discuss topics like driving cost efficiencies, project prioritization, building a strong culture and fostering talent, and the future of in-house agencies.

Paving the Path to In-Housing Success

March 13, 2019 | 3:45 PM EST

The decision to go in-house should not be taken lightly, nor is a 100% in-house model right for every organization. Marketers who jump in without building a thorough business case for change are likely to struggle; a smooth transition requires planning, prioritization, and patience. In this session, Bayer and MightyHive will break down the organizational choices that, when examined preemptively and thoughtfully, will pave the path to in-housing success. We’ll consider how to decide what to bring in-house, cost calculations, managing expectations, partner selection, hybrid resourcing models, and more.

Add to Calendar: Google, iCal

SPEAKERS:

Meet the Team

Interested in learning more about how you can take control of your digital future? Schedule a time to meet with the MightyHive team onsite by emailing ana@mightyhive.com. We look forward to seeing you there!

See What Makes Confident Marketers Tick

If you’ll be onsite, be sure to visit the MightyHive table to get a cozy gift and a first look at our new report: The Data-Confident Marketer. We partnered with Advertiser Perceptions to survey 200 marketing decision-makers to find out what makes data-confident brands tick. Pick up our report to see how you measure up.

WHERE
The Ritz-Carlton, Orlando Grande Lakes
4012 Central Florida Parkway
Orlando, FL 32837

WHEN
Wednesday, March 13 – Friday, March 15, 2019

Attribution Solutions: Where to Start When Digital Metrics Fall Short

 

“It’s important for us to help our clients build the framework to identify how their KPIs tie back to their marketing and business objectives.”

– Cullen Urbano, Enterprise Consulting Lead, MightyHive

Attribution is an integral component of any successful marketing plan. But where should marketers start with attribution modeling, and what happens when digital metrics fall short? On January 17, practitioners from across the industry met at MightyHive NYC over pizza and drinks for a deep dive into the triumphs and challenges of digital analytics, and where advertisers often go wrong.

Rachel Adams, MightyHive’s Director of Accounts, moderated a panel entitled Attribution Solutions: How to be a Hero when Attribution Models Fall Short. On the dais for the evening were Ben Rudolph and Emma Tessier, both MightyHive Project Leads, as well as Cullen Urbano, an Enterprise Consulting Lead at MightyHive. Ben, Emma, and Cullen drew on their experience with clients and their in depth industry knowledge to provide a well-rounded perspective about the best strategies for attribution modeling.

attribution panel

Left to Right: Rachel Adams, Director of Accounts; Cullen Urbano, Enterprise Consulting Lead; Emma Tessier, Project Lead; Ben Rudolph, Project Lead

We Are Gathered Here Today…

Attribution is a hot topic. The MightyHive office was packed with people who voluntarily passed up a night of binge watching Netflix to talk about it. But what makes attribution so challenging for advertisers in the first place?

Tech Companies Aren’t Great at Sharing

Our panelists all cited tech limitations and walled gardens as major factors that make it tricky to figure out how marketers should optimize their media spend. As Ben pointed out, “In the ecosystem a lot of players want to demonstrate their specific value, so they put up walls and are unwilling to share data that will give marketers a more complete picture.” He continued, “There’s also no north star for advertisers to look to that isn’t last-touch, so it can feel risky or intimidating to look at different models.”

Also, Robots Aren’t Perfect

Another often-overlooked factor when dealing with high-tech, automated solutions is human oversight. Cullen stressed the importance of evaluating every model with a human gut-check. “If you do that, you can avoid instances where an MTA model might recommend a mass reach partner with sub-20% viewability and +30% frequency.”

Rachel echoed: “Even though all the decisions we make are highly data-driven, at the end of the day there’s an element of ‘does this feel right?’ Does something seem off? Are these impressions even viewable? Is there an instance of fraud? Are we utilizing all of the verification tools we have at our disposal, etcetera, that only a human can evaluate.”  

But Humans Aren’t Perfect Either

However, before even talking tech, all agreed that marketers need clearly defined KPIs and a full view of business objectives before they can tackle attribution modeling. Emma noted, “So many clients freeze when you ask, but they need to understand their KPIs and the platforms they’re running across. Someone who understands multi-touch attribution realizes the need to address the full funnel, whereas someone who’s not as intimately exposed might think it makes sense to allocate budget to last-touch because that’s what they see as driving conversions. They don’t understand how different touchpoints work together.”

Cullen and Emma both pointed out a common problem: clients who optimize towards the wrong goal. For example, if an advertiser makes most of its sales offline, they may be better served by optimizing for top funnel brand awareness than web traffic.

Attribution Challenges IRL

When asked about interesting attribution problems they’ve helped clients crack, Ben referenced a client with the “pragmatic goal of trying to be less wrong.” This comment elicited a chuckle from the audience, but he continued, “It’s a great way to think about attribution because there’s never really an end-state. This client wanted to move away from last-touch, so we shifted to a fractional model which was very successful for them.” Although the fractional model helped the client optimize budget, it’s still an iterative process as the ecosystem and consumer behavior are constantly in flux.

Cullen and Emma both pointed out a common problem: clients who optimize towards the wrong goal. For example, if an advertiser makes most of its sales offline, they may be better served by optimizing for top funnel brand awareness than web traffic.

Similarly, Emma recently worked with a client who was focused on brand awareness, but stated KPIs as ROI and sales. Emma guided the client towards an MTA model that incorporated offline and third-party vendor data to create a less biased full view across channels.

There’s Hope Yet

Though tech limitations and walled gardens can present roadblocks for marketers, tools like Amazon Attribution, Google Analytics 360, and tech stacks that move away from proxy metrics are a step in the right direction for advertisers trying to marry disparate data sources.

MightyHive is Up to the Task

The MightyHive team, well-versed in Salesforce and Amazon Advertising solutions and globally certified across the Google Marketing Platform and Google Cloud, is uniquely qualified to help marketers solve complex attribution challenges. In fact, when asked what’s most exciting about working at MightyHive, the panelists all indicated that they love tackling new and interesting problems.

“We’re in a new frontier where we get to come up with processes to help companies figure out problems no one else is helping them solve.”

– Emma Tessier, Project Lead, MightyHive

“One Size Fits All” Isn’t MightyHive’s Thing

One such problem, which Cullen and the MightyHive consulting team recently addressed, was working to onboard a client’s first-party data to make it available to different attribution systems. While the most straightforward answer was to use an onboarding partner, sometimes that can yield match rates below 30-40%, which makes it difficult for advertisers to glean useful insights.

“We did some interesting things where we combined several approaches,” Cullen described. “We started with an onboarding partner, and for unmatched records, we used third-party and DMP data to model out lookalike audiences. We also included second-party data partnerships, and rounded them out by amplifying first-party login info, married to offline data where possible.” Using this strategy, the team was able to produce much more indicative results, giving the advertiser a 70-80% match rate.  

We’re Hiring… Big Time

If learning about new ways to approach complex digital analytics challenges excites you, MightyHive is hiring around the globe! Check out our careers page to learn more.   

Video: Five Factors to Consider When Going In-House

Watch “The Spectrum of Control” (page opens in a new window)

At AdExchanger’s Programmatic I/O in New York, MightyHive CEO Pete Kim took the stage to offer guidance to marketers looking to go in-house. His presentation addressed five factors marketers should consider when evaluating where they fall on the Spectrum of Control—a framework for in-housing—along with actionable next steps.

A Fundamental Shift

Pete highlights the fundamental shift that we are seeing in consumer viewership and media consumption habits where attention is a commodity:

“Consumers today can watch anything they want, listen to anything they want, read anything they want, consume any media that they want, at the touch of a button. Perfectly integrated, perfectly synchronized across every device that they own.”

– Pete Kim, CEO, MightyHive

As Pete attests, consumers expect more out of their screen time and by extension, their ads. This presents new challenges for advertisers who are battling low consumer sentiment around ads in general.

In order to create more meaningful, personalized, targeted ads that meet rising consumer expectations, advertisers must be smarter about how they deploy their vast amounts of data. This requires enhanced and unified control over media planning, data, and analytics. For many companies, however, bringing everything in-house is neither  a realistic or necessary solution.

Control is Not Binary

Most brands feel that in-housing is an all-or-nothing insurmountable hurdle, but Pete proposes that there is no one-size-fits-all solution. Rather, there are various levels of control advertisers can have for in-housing to accommodate their available resources and technical expertise.

in-house spectrum of control

These options range on a sliding scale from completely outsourced, which gives advertisers little transparency but also requires fewer brand resources, to fully in-housed, which offers full control but requires deep technical expertise or training and headcount resources.

Five Factors to Consider When Going In-House

Next, Pete introduces five points marketers must consider to assess where they belong on the Spectrum of Control:

in-house factors to consider

Depending on the combination of factors that apply to a specific advertiser, this framework is how marketers can determine the right combination of in-housing and outsourcing for their brand.

Where to Start

Pete then provides a tangible roadmap for marketers once they have evaluated where they fall on the Spectrum of Control.

“When done correctly, this can well and truly revolutionize our industry, address many of the huge issues we face every day, and ultimately will help the businesses that will win tomorrow figure out how to talk to their customers today.”

– Pete Kim, CEO, MightyHive

Watch Pete Kim’s full “Spectrum of Control” session for actionable steps to get started with in-housing.

Did you know 67% of marketers think they’ll have first-party data solved within 18 months? Request a copy of our upcoming report about how enterprise brands are activating their first-party data to see how you measure up.