Tag: Digital Advertising

WEBINAR: Watch Google’s “Digital Transformation” Session with Sprint, Harvard and MightyHive. Get Your FREE Copy of the Sprint Case Study


Last year, telecom giant Sprint (now T-Mobile), completed a digital transformation that caught the attention of Harvard Business School. Seeing it as an example of a business trend marketers should pay attention to, Harvard published a comprehensive case study for its graduate students in July, and Google brought it all to life for Part IV of its “Digital Transformation” series on October 29.

Google assembled an online panel comprised of MightyHive CEO, Pete Kim, Harvard Business School professor, David Bell, and T-Mobile SVP Digital Emerging Products, Rob Roy. Each shared their unique experiences and views on the MightyHive/Sprint partnership, including technical and personnel challenges, and how the case study reflects a business challenge faced by many brands today.

Watch Digital Transformation with T-Mobile, MightyHive & Harvard Business School


In 2016, Sprint set out to simultaneously address changing consumer habits and improve operational and advertising efficiency. “When the CEO tells you to figure out how to do the largest Fortune 500 transformation, you have to come up with some unique ideas using goal posts that are really far out,” Roy shared during the webinar. “I challenged the team, but the effort [came from] the individuals who wanted to do something really unique…that hadn’t really been done at [this] scale…and do it all while trying to grow the business.”

Roy set out to establish a cultural change that would put Sprint on even ground with companies—partners and competitors alike—that were born in the digital age. “How do we digitally transform the people [so that] digital runs throughout the organization?” posed Roy. “We created a bunch of new processes and experiences within the larger part of the organization and that led us to the next steps; bringing media in-house, building unique apps, etc. We needed the whole company on board and not just a digital team trying to hit a couple KPIs and we were very pleased with the results.”

“We needed the whole company on board and not just a digital team trying to hit a couple KPIs”

– Rob Roy, SVP Digital Emerging Products, T-Mobile 

Professor Bell echoed Roy’s assessment of the need for cross-department collaboration: “Understanding business situations requires understanding how everything fits together,” he said. “Management needs to be cross-function not just within the functions, and I believe this case study shows that.”

Pete Kim added that digital transformation is unique to each company. “We didn’t come into [the partnership with Sprint] with an assumption that in-housing was the right solution,” he explained. “There are many ways to skin the digital transformation cat, if you will. From the broad spectrum of options—total outsourcing to 100% in-housing—the first thing is to understand where on that spectrum each particular client belongs. And that is an assessment [of the] business itself and the preparedness of the teams.”

Get your FREE copy of the Sprint case study published by Harvard Business School in July. 


Both Kim and Roy recognized that digital transformation requires every company to charge into uncharted territories. “The people that we brought in are the type of people who are excited by the challenge and don’t want to rest on norms,” explained Roy. “We created something very unique that has given us more and more opportunity as we peel back the onion. I had an amazing set of individuals and partners in MightyHive and others to actually make this thing happen.”

“The next five to ten years are going to be a reckoning,” said Kim. “People should understand that [digital transformation] is really going to happen and it requires change agents who have the vision, courage, and authority to move.”

Get your free copy of the case study and watch the session to learn more:

WATCH “Digital Transformation” to hear Sprint’s stories. 

DOWNLOAD the HBS Case Study to learn how Sprint executed a complete digital transformation.

VIEW the Slides from the Digital Transformation session.


Breaking Down the S4 Fellowship Program with Pete Kim


Innovation happens when fresh thinking finds new methods, mediums or connections—and it’s only amplified by diversity of background and experience. Still, the technology field historically lacks the diversity needed for true innovation–a problem that’s compounded by the impact that digital has on all aspects of our lives, ranging from education to work to socialization and more.

That’s why we’ve built the S4Capital Fellowship Program, which aims to mitigate these challenges by empowering exceptional students from traditionally underrepresented communities to leave their own mark in shaping the path of technological innovation.

To better understand the program’s significance, we checked in with Pete Kim, who is Co-Founder and CEO at MightyHive and one of the S4 leaders that Fellows can expect to apprentice with.

What’s the S4 story to you – why do you personally care about what we do?

Pete Kim: To me, the S4 story is all about transforming a critically important global industry that is ripe for change. Clearly, this means that we will deliver groundbreaking results for our clients and our industry.

But what is just as exciting to me is what this will mean for our people: we’re creating an awesome and exciting career for our employees, who ultimately are the key in delivering amazing results for our clients.

While doing this, we’re driving and becoming a part of the many changes that we’d like to see in our culture and society, which the S4Capital Fellowship Program is a testament to.

What’s the fellowship story, and how did it come about?

PK: The fellowship is one of the several responses that S4 has made to assist in the cause of diversity, equity and inclusion, and was spearheaded by Sir Martin Sorrell. With the fellowship we’re saying to under-represented students and professionals in tech that success at a global powerhouse like S4 is achievable for them. The door is open, come on in.

Why is the fellowship important to you, and what will your contribution be?

PK: I firmly believe in both the power of diversity and inclusion and the moral imperative that every company has to do its part to change the world in a positive way. All of the teams at S4 have made public commitments to move forward in this regard, and this initiative is one example of how we’re keeping our word.

What should the fellows expect?

PK: A lot! This is a transformative experience that provides the opportunity to learn about an industry from the very best–and in the process, jumpstart a career. And that word “opportunity” is key, because much will be expected of the Fellows to do the hard work of walking successfully through the door that has been opened to them.

Along the way, they’ll gain access to different parts of the business, as well as a group of executives who span different disciplines, far in excess of what one would expect in a typical fellowship program.

What do you want the Fellows’ impact to be on the company and its clients?

 PK: The Fellows will serve as role models for youth in the field, and I hope they’ll inspire the next generation of talent. Our goal with the program is to show that diversity, equity and inclusion is good for our people, our communities, and the bottom line. I’d like to see their work amplified to showcase these benefits to our clients, employees and to the world at large.

For the inaugural class of the S4Capital Fellowship Program, we’re seeking U.S. graduates from Historically Black Colleges and Universities who boldly question the status quo and rip up the rulebook when confronted with challenges, using creativity and analysis to launch new ways of thinking, working and doing. If you’re energized to build on the foundation of a new era, we encourage you to apply here.

WEBINAR: The Future Begins in Q4—How a Q4 Amazon Strategy Sets the Stage for 2021 (and Beyond)

On October 7, Live with MightyHive invited John Ghiorso, CEO of the industry’s top Amazon consultancy, Orca Pacific, for a topical discussion about Q4 online shopping trends. Currently, eCommerce is experiencing 40-50% YoY growth driven by social distancing restrictions connected to the COVID-19 health crises. And with few signs of letting up, every analyst is predicting record-breaking online sales in Q4. But Ghiorso is anticipating more than just holiday sales; he has his eye on sustained growth driven by new customers, new loyalties and new shopping habits.

Consumers are no longer buying six months of toilet paper…but they are doing a lot more online purchasing and that has not stopped or subsided in any significantly way.
– John Ghiorso, Founder & CEO, Orca Pacific

Orca Pacific is advising its clients that Q4 2020 is a rare opportunity to earn customer loyalty at scale. From now through the holidays, Amazon sellers — small and large — will interact with customers who are either new to online shopping or buying items they once exclusively purchased in-store. New shopping habits are clearly forming so when these new customers have good online shopping experiences, it can yield loyal customers for years to come. Not only do good customer reviews help, but those who invest in driving traffic through aggressive advertising strategies will see their organic ranking climb.

We saw a huge spike (in online sales) and then a plateau at a level that is much more significant than it would have otherwise been….and that trend is not stopping or slowing down.
– John Ghiorso, Founder & CEO, Orca Pacific

Join John Ghiorso and MightyHive’s Director of Content Marketing, Adam Remson, as they outline Amazon marketing techniques and the many ways Q4 2020 is a pivotal one for brands. 

Check out the Video and Download the Slides

Please don’t hesitate to contact us with any questions.

Revisiting Measurement Strategy with the Advent of GA4

Are your measurement strategy and tagging implementation aligned? It’s OK, you’re in a safe space here—we know that keeping technology, tactics, and strategy in 100% alignment is nearly impossible in practice. Fortunately, the advent of Google Analytics 4 (or “GA4,” formerly Google Analytics for App + Web) is an ideal time to approach a strategic measurement review.

Which came first, your tags or your measurement strategy?

Which came first, the chicken or the egg? Wikipedia refers to this question as a “causality dilemma”—we can’t decide which event is the cause, and which is the effect.

Which came first, your tags or your measurement strategy?

Do any of these options sound familiar?

  • There is no strategy
  • The strategy and tagging bear no relation
  • The strategy is retrofitted to match the organically grown, free range, tag management

There is no shame in accepting that the strategy might not be up to date with the current tagging implementation. Tactical measurement is more volatile, for sure. Tag management is meant to help you move fast! However, lack of a strategy, significant disconnect between strategy and tagging, or strategy adapted to fit the tags (as opposed to the right way around) are not acceptable and must be addressed.

“Some people spend their entire lives waiting for the time to be right to make an improvement.”

James Clear, “Atomic Habits: An Easy & Proven Way to Build Good Habits & Break Bad Ones”

An opportunity presents itself

The advent of GA4 (formerly Google Analytics for App + Web) is an ideal time to approach a strategic measurement review. Don’t think this means you’re going to throw away your existing Universal Analytics (UA) implementation and start again. Far from it. An existing reference point to work from is a valuable asset.

You need to consider the following in your current tagging in order to decide the correct tactical and strategic alignment:

  • what currently works and aligns with strategy
  • what’s currently broken and is misaligned
  • what’s missing from tagging and/or the strategy
  • what’s bloat and simply needs to be removed

Fix the broken stuff, fill in the gaps, and ditch the unnecessary to trim down and align your tagging and measurement strategy.

Connect measurement strategy and implementation

As a quick refresher, let us recall what is meant by a “measurement strategy”:

  • Goals
  • Audiences
  • KPIs

A measurement strategy is a formalisation of what is measured, why, and what success criteria look like. The lack of an objective set of measurements is a key cause of digital marketing failure.

Accepting that the current measurement implementation and strategy need to be reviewed and adjusted, this provokes a number of questions:

  • How did we end up here?
  • How do you fix it?
  • Why do you fix it? What’s the value?
  • How often do you realign strategy and measurement?

In the absence of any formalised process for tactical and strategic data alignment, measurement tactics will naturally diverge from the ideal mandated by the organisational aims.

A good starting cadence for a process to address this issue is quarterly. This will be driven by the pace of change in your tag management, rather than your organizational strategy.

Start now.

Industry guru Avinash Kaushik has already written what needs to be written on measurement strategy so I won’t repeat it here.

The golden opportunity at hand is to reflect on the legacy measurement, consider what is possible with GA4 and ensure that the next generation of digital analytics instrumentation is as aligned with your global strategy as possible. Go beyond “fit for purpose” and strive for “OMG, this is digital marketing performance visibility I never thought possible!”

Priceless advice—don’t get this bit wrong

When you embark on this process, be aware that UA tag types no longer exist. There is only one tag: an event. GA4 is event driven and user-centric. The GA4 core measurement is based on the concept of the event which means event name choice is critical to success.

Use the GA4 event name to convey the meaning of the event. This needs strategic alignment of course, but, as much as possible, it is important to use the GA4 automatic, enhanced and recommended events before committing to a new custom event. This ensures the best/right reports are available for your data out of the box. Using customised event names might not enable all reports.

Flow chart

In conclusion

To not have a strategically aligned measurement approach is to court disaster. Recognising that Google Analytics is changing, and in so many ways, for the better, is to embrace a fabulously valuable opportunity to address strategic alignment and remedy tactical issues in one swoop.

Learn about GA4, and use it to plan the migration from UA. Build a measurement roadmap that complements the digital marketing plan. Be proactive, rather than reactive in measurement and strategy. Draw these components into a repeatable process, and ensure tagging remains aligned with strategy.

WEBINAR: ‘Mastering Creative Effectiveness’—A Roundtable with Google, MediaMonks, and MightyHive

Mastering Creative Effectiveness

On September 16, Live With MightyHive featured a conversation on Creative Effectiveness. Joining me in this episode were Ryan Tetuan, Head of Creative Solutions, Media Platforms at Google and Louise Martens, Global Head of Embedded Production at MediaMonks. The discussion was interesting and offers viewers some actionable tips on where to get started.

What does Creative Effectiveness mean?
“Does the work, work? Are our efforts paying off? Are we hitting the goals that we set out together with brands?”
– Louise Martens, Global Head of Embedded Production, MediaMonks

It didn’t take long for us to dive into an in-depth discussion about what Creative Effectiveness really means. We went on to highlight the greatest opportunities for brands and provided recommendations on how to get started with creative. Above all, collaboration is key to your team’s success.

How can creative and media buying work better together?
“As we are testing new tactics, what new creative ideas can we put out there? Hey, we just did this new research on the creative side and we now understand what consumers are responding to – Can we actually target that micro-moment using the targeting capabilities of DSP?”
– Mitchell Pok, Director, Creative Services & Technology, MightyHive

According to a recent study conducted by Google and Bain, creative is 1.5x more effective when developed collaboratively than it is when it’s created in separate silos. Nielsen states that 56% of a campaign’s performance is due to creative. The research shows that mastering Creative Effectiveness can drive meaningful results for your campaigns and broader business goals.

In this episode, we also identified various roadblocks we see across the brands we know. These roadblocks range from the briefing process to the democratization of campaign performance data.

What’s standing in the way of Creative Effectiveness?
“I had media teams within 20 yards of me. There weren’t any physical walls and my interaction with the media team was essentially an email from them with an Excel spreadsheet of sizes of ads to build. That’s it. No audience, no contextual data.”
– Ryan Tetuan, Head of Creative Solutions, Media Platforms, Google

Check out the video to join the discussion and find ways you can start mastering Creative Effectiveness today. To view the Google Marketing Platform Solutions Guides, click here.

Please don’t hesitate to contact us with any questions.

WEBINAR: Slides and Video for ‘The Essential Role of Data Taxonomy in Bayer Digital Marketing’


For the August 25 Live with MightyHive episode, I was pleased to be joined by special guest Jeff Rasp, VP Digital Platforms, Channels & Capabilities at Bayer. He and I discussed the many benefits of an airtight marketing data taxonomy and Rasp explained how consistent campaign naming conventions are the foundation of a Bayer in-house team that earned the AdExchanger award for “Best In-House Media Operation” in 2020

According to a recent report conducted by Dataroma, 57% of marketers spend a week out of each month manually integrating data. As part of the MightyHive and Bayer partnership, Bayer established a sound taxonomy early in the in-housing process to essentially automate that task. And in “The Essential Role of Data Taxonomy in Bayer Digital Marketing,” Rasp explains how he distilled the KPIs of multiple departments into a unified naming convention capable of great versatility. 

Today, the Bayer marketing team generates insights in minutes, not days. And in this episode, Rasp outlines how his team pivots to accommodate the diverse reporting needs across the company. Watch the video to see Rasp and I discuss: 

  • How to create a data framework and hierarchy
  • The power of a well-planned media taxonomy
  • Data governance and the importance of consistency




Thanks for watching! If you have questions about the role of marketing data taxonomy in your organization, please contact us.



Server-Side Google Tag Manager Deep Impact


Before we dive into server-side Google Tag Manager (GTM), I’ll prefix the meat of this post with a caveat: always respect user privacy

Any data collection techniques discussed here must be applied righteously and not as a workaround to circumvent data collection consent regulation.

10,000 Foot View

Here’s a familiar situation – Google Tag Manager as we’ve known it for years.

Your container is loaded on all pages, or screens in your site/app, and based on trigger events, data is sent to first- and third-party endpoints.

It works, it’s fine, but it’s not perfect. Tracking blockers, JavaScript failures, many, many requests to endpoints, and inefficient JavaScript are all risks, and potential performance problems that can lead to data quality issues.  

Server-side GTM moves the tag vendor request from the client to a server—a server on Google Cloud Platform living on a subdomain of your site. The container loaded in the browser/app still has tags and still sends a request but has way less code, sends fewer requests, isn’t necessarily affected by anti-tracking software, doesn’t send the user’s IP address to third-party tag vendors, and first-party cookies are correctly set in an ITP compliant manner.  

Out of the Box – What’s Cool?

There’s a lot to be excited about with server-side GTM in that, on the client side, it’s all very familiarbut way better! The “traditional” digital marketer can still set up their Facebook tag(s) with the same triggers, and deploy Floodlights as required. Same, same… but different.

As mentioned earlier, rather than sending data to the tag vendor endpoint, it’s sent to a subdomain. For example, if you’re on www.mysite.com, server-side GTM will send data to tracking.mysite.com, a subdomain you can have configured.  

And that’s great because…?

  • It respects user privacy: The user’s IP address isn’t sent to a third party.
  • It preserves data quality: Tracking prevention doesn’t happen on requests to your own domain.
  • It lightens code bloat from the client side: The tags require less work on the browser, shifting the workload to the server instead. This means what remains in GTM on the browser does less, so the site runs faster.
  • It consolidates requests from the client side: You can send multiple requests from the server based on one request from the client.

At MightyHive, we strongly advocate for focusing on what’s best for the user, not the ability to foil or circumvent anti-tracking software. Reminder: act righteously, not selfishly. As it stands now, data is collected, not captured. In the future data will be exchanged… Think about that for a minute.

Deeper Impact

Have you noticed that tracking requests are sent to your domain and not a third-party domain? The data collection workload is moved to your infrastructure.

Does that feel like just going back to web server logging? How different is this from web server logging?  


Analytics data is formatted (sessionized), cleaned (PII removed), integrated (joined with data from Google Ads, Search Ads/Display & Video 360) and presented ready to perform its function: analysis and optimization of all aspects of the online business, which, let’s face it, is all about better marketing.  

Web server logs don’t collect all behavioral data. Typically, log-level data isn’t integrated with marketing channel data, meaning there’s no feedback loop for activation of the data. 

But! There are similarities between server-side GTM and web server logging. The web server receives a request, typically for a page, builds the page content and responds, possibly setting first-party cookies along with the response. The server-side GTM endpoint also receives requests, and responds, potentially with cookies (but with less content).

Now… the web server knows what page it’s returning.

It knows what data to render on the data layer to record a transaction (for example). 

The data layer is picked up by a tag firing in the browser and then sent back to the tracking endpoint. 

The end point then takes the same data and fires it off to Google Analytics (GA) to complete the round trip and get your analytics data recorded. 


Wait one minute. If the web server knows it’s rendering a “thank you” confirmation page, and it knows what data to render on the data layer, why bother sending this to the browser for the browser to just send it back to the tracking end point and then to GA?  

Why not remove some steps for efficiency? The web server knows it is rendering a confirmation page. So it builds the exact same request the browser was going to, and sends the GA transaction data straight to the tracking end point. Cut out the client round trip.

It’s quite normal to fire off conversion tags, Floodlights, FB pixels, Adnxs, TTD, and so on to record transactions. Don’t send those to the client to handle. As the web server responds with the confirmation page, send those requests straight to the tracking endpoint. The endpoint responds with the details of the cookies to set, and the web server sends those with the confirmation page content in the response to the client.

Think how many marketing tags and tracking pixels fire on page level events. How many tags actually need to fire on the client? How many tags don’t even need to be exposed to the browser? What if, just maybe, you only had page-level event-triggered tags? Maybe you only need page-level tracking if you’ve removed all of your data bloat? Then you don’t need to CNAME the tracking subdomain, you can restrict access to your tracking endpoint to only allow your web server to access it via https (think IP range restriction). That’s a bunch less complexity and a fair amount of moving parts removed from the solution.

Simpler is better. No code is better than no code, as the saying goes.

In Conclusion

The server-side GTM solution offers a good and correct solution to digital analytics measurement. It’s good because data quality can be improved, user privacy is further protected, and significantly, it’s a step towards doing less work in the browser, meaning sites and apps get faster.

Thinking about the possible solutions the technology offers, with the right motivation in mind, demonstrates how versatile the solution is, how much power is available and what avenues are still to be explored to leverage first-party data.


WEBINAR: A Discussion with Ace Hardware About Offline Data and Online Marketing


**Scroll down to watch the video**

How Ace Hardware is Using Offline Data to Measure its Digital Marketing

A recent Google report titled “How Consumers Solve Their Needs in the Moment,” cited 76% of people who search for something nearby on their smartphone visit a related business within a day. And 28% of those searches result in a purchase. “That’s significant,” said Mark Lowe, Director of Digital Marketing at Ace Hardware. “So it is critical for us to have the [online customer experience] be as helpful as possible.”

Lowe is a seasoned digital marketer and on August 4, he provided a glimpse into how Ace Hardware is adjusting to shifting consumer habits during an eMarketer “Tech Talk” webinar titled “How Ace Hardware is Using Offline Data to Measure Digital Marketing.” Along with Myles Younger, Senior Director of Marketing MightyHive, the two discussed how he balances nationwide digital trends with in-store buying at the retail level.

Ace Hardware generates a significant amount of first-party data from its website and its stores. By partnering with MightyHive, they reimagined ways for online and offline data to inform each other. “That means a very pure approach to data since many data sources need talk to each other,” explained Jack Pace, Project Lead at MightyHive. “Offline data from the store, online data from the site and app, franchisee sales data, manufacturer data from the thousands of SKUs carried throughout the chain — each store is different.”

Lowe is excited by the possibilities. “We are getting good insight into how many people are going into the store to pick up their online orders as well as the attachment sales when they are making their pickup,” explained Lowe. “And we are really leveraging several tools such as Google store visits and store sales direct from Google to connect the dots and understand the impact across all channels.”

With 4500 retail locations, a robust online presence, and thousands of SKUs, Ace Hardware had a unique challenge with its data but the efforts are paying off. “As data-driven marketers, we really want the same level of precision that we have with our online measurement with our offline,” explained Lowe. “There is going to be a certain level of extrapolation but it’s all about getting to the point where you can make actionable business decisions.”

In this eMarketer “Tech Talk” webinar you will learn about:

  • The Ace Hardware digital marketing tech stack
  • Successes, opportunities, and challenges in measuring the offline impact of digital campaigns
  • The role web UX can play in collecting and growing first-party data


We Commit to Change

Recently, S4Capital made a strong commitment to foster diversity, equity, and inclusion among its 2,500+ employees. Although in some cases our statistics are better than national averages, we recognize there is still work to be done in this area.

Committed to Diversity, Equity & Inclusion

MightyHive believes that diversity and inclusion are essential to its success. Differences in ideas, opinions, and experience add depth to the work we do, enriching the lives of our people and our work for clients.

Committed to Accountability

We have chosen to make our US diversity data public. Looking at the stats:

commit data ethnicity

By ethnicity: 40% of our US employees are ethnically diverse, the most underrepresented groups being Black Americans, Hispanic or Latinos, and Native Americans.

commit gender data

By gender: 48% of US employees identify as women, with 33% at the executive level, and 52% identify as men.


Committed to Change

Alongside S4Capital and our sister companies, we commit to improving diversity, equity, and inclusion at MightyHive. We aim to promote an inclusive culture where all are welcome to share their expertise and further their career. We are committed to: 

  • Regularly tracking our ethnic diversity statistics to hold ourselves accountable and updating these statistics at least once every year
  • Increasing the diversity of our employee base, specifically the number of Black employees, to match population levels in the communities where we work 
  • Increasing and promoting gender and ethnic diversity at all levels of our company, especially in leadership roles
  • Continuing to build on our employee training requirements with a focus on allyship, anti-racism, anti-bias, and other initiatives that promote racial equity
  • Regularly assessing our culture, practices, and company policies to ensure we are maintaining and supporting an equitable environment for all 
  • Staying open to learning from one another, both internally and in our industry, as we aim to improve racial and social justice for everyone
  • Continuing to support our Employee Resource Groups (ERGs) 
  • Participating in S4Capital’s fellowship program, and developing local internships to recruit minority graduates and non-graduates to train with us
  • Conducting a gift matching drive to contribute to some of the major US nonprofits that support racial equality and justice.
  • Posting our progress towards these commitments quarterly on social media

We stand committed. We are, and will be, transparent and accountable. We’re in it for the long haul.


Digital Hygiene: Fighting Data Bloat


Some years ago, as digital storage grew more affordable, the attitude towards data by many companies was to “store everything.” Every. Single. Data. Point. 

Next came “big data” and cloud computing, which brought even more data, more computing power, and ostensibly more opportunity and insights.  As a result, data consumption skyrocketed, driven by the Internet, social networks, and digital services.

To paraphrase my guru Avinash Kaushik, we now have more data than God ever intended anyone to have. 

The instinct to store everything is understandable. Why throw away data? But there have been a few unforeseen effects:

  • It increases the workload associated with data quality assurance
  • It increases data processing times
  • It makes data sets more complex and more difficult to work with
  • Most of the data is irrelevant to business analysis

The decision to keep all the data was an easy one. Discerning which data points should be considered is difficult. This consideration phase will be implemented either as companies are specifying a data project (BEFORE), or as they introduce a new release of their digital assets (AFTER).

For mature audiences only

Imagine you’re building the specification for your project and figuring out how to measure project success. You will most likely consider the following KPIs:

  • Key feature usage rate (conversion rate)
  • Marketing effectiveness (budget, cost per acquisition)
  • Vanity metrics (volume, users)

Sounds too basic? Fair enough. And yet that’s a great base to work from! 

Important Tip: Your project must be in sync with your organization’s maturity level.

First, you need to make sure the basic data you intend to collect from your site or app resonates with your product managers, your marketing team, or your analysts. They need to understand how these basic numbers can help shape your product or marketing strategies. 

Then, a specification document must be established. A Data Collection Bible of sorts. Call it a tagging plan, a data collection blueprint, a solution design document… get creative! That document will not be set in stone. It will evolve with your company as you enrich your data set to meet your measurement requirements. Make sure to include significant stakeholders in that process, or else…

Only after you’ve gone through a thorough data specification phase can you consider enriching your data during subsequent development cycles. Data enrichment will either be:

  • Vertical: more metrics to measure specific user events
  • Horizontal: more dimensions/attributes to give metrics more context

Keep enriching your data to assess the KPIs that support the measurement of your business objectives. Give them as much context as you can so the analysis is as relevant and actionable as possible.

Does your data spark joy?

All this talk about enriching your data sounds great, but you may be at a stage where you’ve collected way too much data already. Arguably, getting a ton of data means getting the fuel to power machine learning, artificial intelligence, or any reasonably advanced data processing.

Having said that, too much unidentified/non-cataloged data will ultimately yield confusion and storage/processing costs. For instance, if you have a contract with a digital analytics vendor (say Adobe or Google), it is very likely you’re paying a monthly/yearly subscription fee based on the number of hits your system collects and processes into reports, cubes, and miscellaneous datasets. Additionally, digital marketing teams are not known for questioning the status quo when it comes to data and tracking, in particular.

If you combine both facets of data cleanup, we’re looking at an optimization campaign that turns into a cost-saving effort. This is where you as a company should start asking yourself: “do I really need that data? Can my team function without measuring metric X and attribute Y?”

To borrow from Marie Kondo’s konmari method, you should keep only data points that speak to the heart. Identify metrics/attributes that no longer “spark joy,” thank them for their service before brutally disposing of them with a firm and satisfying press of the DELETE button.

How can you tell whether you should discard a specific data point?

This requires a bit of investigation that can be done in your data repository by looking at your data structure (column names and values for instance). If you cannot make up your mind, ask yourself whether one particular data point really “sparks joy,” or in our case, drives analysis and can be used as a factor in machine learning. In fact, this is a great occasion to actually use machine learning to find out! 

Feed your data set into R/Python (insert your favorite machine learning package here) and look at the results:

You could also look at factor analysis another way and see where a specific factor really contributes to performance, metric by metric:

Once you’re done analyzing which data points still belong in your data architecture, it’s time for pruning. If you have made the decision to delete existing data, this can be as simple as deleting a column or a set of entries in a database, data lake, or data repository. But that’s only for data you already collected. What about data collection moving forward? 

If you want to change the way data is collected, you need to go konmari on your digital assets: web site tracking, mobile SDKs, OTT devices. Using a tag management system (TMS), you can start by deactivating/pausing tags you no longer need before safely deleting them from future versions:

From a management perspective, stakeholders need to make themselves known and express clear data requirements that can easily be retrieved. That way, when you prune/retire data that is deemed to no longer spark joy, you’re not inadvertently sabotaging your colleagues’ reports.

And this is why you needed that Data Collection Bible in the first place!

Which data stage are you at? Before or after? Basic or complex? Don’t hesitate to contact MightyHive for a data maturity audit or a digital analytics health check!