A Map or a Matrix? Identity Management Is More Complex By the Day

A newly published white paper on how advertisers and brands can recognize unique customers across marketing platforms underscores just how tough this important job is for data-driven marketers.

As technologists and policymakers weigh in themselves on the data universe – often without understanding the full ramifications of what they do (or worse, knowing so but proceeding anyway) – data flows on the Internet and on mobile platforms are being dammed, diverted, denuded, and divided.

In my opinion, these developments are not decidedly good for advertising – which relies on such data to deliver relevance in messaging, as well as attribution and measurement. There is a troubling anti-competition mood in the air. It needs to be reckoned with.

Consider these recent developments:

  • Last week, the European Court of Justice rendered a decision that overturned “Privacy Shield” – the safe harbor program that upward of 5,000 companies rely upon to move data securely between the European Union and the United States. Perhaps we can blame U.S. government surveillance practices made known by Edward Snowden, but the impact will undermine hugely practical, beneficial, and benign uses of data – including for such laudable aims as identity management, and associated advertising and marketing uses.
  • Apple announced it will mandate an “opt-in” for mobile identification data used for advertising and marketing beginning with iOS 14. Apple may report this is about privacy, but it is also a business decision to keep Apple user data from other large digital companies. How can effective cross-app advertising survive (and be measured) when opt-in rates are tiny? What about the long-tail and diversity of content that such advertising finances?
  • Google’s announcement that it plans to cease third-party cookies – as Safari and Mozilla have already done – in two years’ time (six months and ticking) is another erosion on data monetization used for advertising. At least Google is making a full-on attempt to work with industry stakeholders (Privacy Sandbox) to replace cookies with something else yet to be formulated. All the same, ad tech is getting nervous.
  • California’s Attorney General – in promulgating regulation in conjunction with the enforcement of the California Consumer Privacy Act (in itself an upset of a uniform national market for data flows, and an undermining of interstate commerce) – came forth with a new obligation that is absent from the law, but asked for by privacy advocates: Companies will be required to honor a browser’s global default signals for data collection used for advertising, potentially interfering with a consumer’s own choice in the matter. It’s the Do Not Track debate all over again, with a decision by fiat.

These external realities for identity are only part of the complexity. Mind you, I haven’t even explored here the volume, variety, and velocity of data that make data collection, integration, analysis, and application by advertisers both vital and difficult to do. As consumers engage with brands on a seemingly ever-widening number of media channels and data platforms, there’s nothing simple about it. No wonder Scott Brinker’s Mar Tech artwork is becoming more and more an exercise in pointillism.

Searching for a Post-Cookie Blueprint

So it is in this flurry (or fury) of policy developments that the Winterberry Group issued its most recent paper, “Identity Outlook 2020: The Evolution of Identity in a Privacy-First, Post-Cookie World.”

Its authors take a more positive view of recent trends – reflecting perhaps a resolve that the private sector will seize the moment:

“We believe that regulation and cookie deprecation are a positive for the future health and next stage of growth for the advertising and marketing industry as they are appropriate catalysts for change in an increasingly privacy-aware consumer environment,” write authors Bruce Biegel, Charles Ping, and Michael Harrison, all of whom are with the Winterberry Group.

The researchers report five emerging identity management processes, each with its own regulatory risk. Brands may pursue any one or combination of these methodologies:

  • “A proprietary ID based on authenticated first-party data where the brand or media owner has established a unique ID for use on their owned properties and for matching with partners either directly or through privacy safe environments (e.g.: Facebook, Google, Amazon).
  • “A common ID based on a first-party data match to a PII- [personally identifiable information] based reference data set in order to enable scale across media providers while maintaining high levels of accuracy.
  • “A common ID based on a first-party data match to a third-party, PII-based reference data set in order to enable scale across media providers while maintaining high levels of accuracy; leverages a deterministic approach, with probabilistic matching to increase reach.
  • “A second-party data environment based on clean environments with anonymous ID linking to allow privacy safe data partnerships to be created.
  • “A household ID based on IP address and geographic match.”

The authors offer a chart that highlights some of the regulatory risks with each approach.

“As a result of the diversity of requirements across the three ecosystems (personalization, programmatic and ATV [advanced television]) the conclusion that Winterberry Group draws from the market is that multiple identity solutions will be required and continue to evolve in parallel. To achieve the goals of consumer engagement and customer acquisition marketers will seek to apply a blend of approaches based on the availability of privacy-compliant identifiers and the suitability of the approach for specific channels and touchpoints.”

A blend of approaches? Looks like I’ll need a navigator as well as the map. As one of the six key takeaways, the report authors write:

“Talent gaps, not tech gaps: One of the issues holding the market back is the lack of focus in the brand/agency model that is dedicated to understanding the variety of privacy-compliant identity options. We expect that the increased market complexity in identity will require Chief Data Officers to expand their roles and place themselves at the center of efforts to reduce the media silos that separate paid, earned and owned use cases. The development of talent that overlaps marketing/advertising strategy, data/data science and data privacy will be more critical in the post-cookie, privacy-regulated market than ever before.”

There’s much more in the research to explore than one blog post – so do your data prowess a favor and download the full report here.

And let’s keep the competition concerns open and continuing. There’s more at stake here than simply a broken customer identity or the receipt of an irrelevant ad.

3 Google Analytics Tips for E-Commerce

There’s a lot more to Google Analytics than looking at basic traffic metrics. These tips will help you make improvements to drive more e-commerce sales from your different marketing channels. 

Many businesses using Google Analytics are only scratching the surface of what Google Analytics can do. By not taking advantage of the platform’s more powerful features, they lose out on getting a lot of valuable insights about their marketing and how to make the most of their budgets.

Covering every aspect of Google Analytics would require an e-book. So in this article, I’ll walk through three steps to get you started and more familiar with Google Analytics.

1. Base Your Website Objectives on Specific Business Needs

You can use Google Analytics to measure how well your website performs in helping you hit your company’s target KPIs. Do not rely on the defaults set up in Google Analytics. Those are meant to cover a broad range of companies, and some of them are not applicable to your business needs.

Instead, take the time to define the important KPIs that your website should be hitting. For example, in addition to online sales, is your goal to generate quote requests for larger/bulk orders? Is another goal to collect email addresses by offering a free report? Where do visitors need to go on your website if they are interested in your products or services?

As you think through these goals, you’ll start to identify conversions that you need to set up in the Google Analytics admin area. This is a critical step that will allow you to monitor the performance of all of your different marketing channels. For example, if your goal is to generate quote requests, then you’ll need to set up a conversion to measure quote requests. Once that’s done, you’ll be able to run reports to see how many quote requests were generated from SEO vs. Google Ads vs. Facebook, or any other marketing channel you’re using.

We also recommend using the audience reporting views to see if your website visitors are actually your ideal customers. You can create customized segments for tracking important demographic points, like age, gender, and location.

Reviewing the information on your visitors may give your more perspective. Maybe your company needs to change its marketing strategy or website layout to resonate more with your target market.

2. Use E-Commerce Tracking

Google Analytics offers a feature called Enhanced E-Commerce. You should see it when setting up your Google Analytics account. Here are a few ways you can use the feature to get a better understanding of the customer journey through your website and shopping portal.

  1. You can track the shopping and checkout behavior of each visitor to your site. That includes product page-views, shopping cart additions and removals, abandoned items, and completed transactions.
  2. You can view metrics, like revenue generated, average transaction quantity, conversion rates for specific products, and how quickly products get added to a shopping cart. You can see what point a customer loses interest in the shopping experience. That lets you focus on tactics that keep them engaged and encourage them to complete a purchase.
  3. You can measure the success of various internal and external marketing efforts meant to encourage shopping and checkouts by visitors. For example, you can see whether the new product banner put up increased conversion rates.

The various reports give you a clear view of the path customers take as they shop on your website.

3. Sync Google Analytics With Your E-Commerce Platform

Many e-commerce platforms, like Shopify, have the ability to quickly sync with Google Analytics. This can save you and your team a lot of time and frustration trying to set everything up manually.

For example, the e-commerce analytics reporting mentioned above requires knowledge of Javascript, if you want to set it up yourself. Always check with the support team for your e-commerce platform to see if they have already synced up with Google Analytics. If they have, then you could be set up in a matter of minutes.

Look Beyond Surface Data

There’s a lot more to Google Analytics than looking at basic traffic metrics. These tips should allow you to gain a better understanding of where you can make improvements to drive more e-commerce sales from your different marketing channels.

  • First, identify your business goals and set up conversions in the Google Analytics admin area.
  • Second, set up enhanced e-commerce analytics either manually or by syncing your e-commerce platform with Google Analytics.
  • And third, review all the e-commerce reports to see which marketing channels can be improved to increase your sales.

Want more tips on how to use Google Analytics? Click here to grab a copy of our “Ultimate Google Analytics Checklist.”

 

Here’s a Website Performance Checklist to Kick 2020 Off Right

Reviewing your website’s security practices, privacy policies, accessibility, and analytics can help improve performance over the course of the year. You can still pledge to get the most from your website. This website performance checklist can help.

No need to abandon all hope if your New Year’s resolutions have already fallen by the wayside. You can still pledge to get the most from your website in 2020. This website performance checklist can help.

None of these topics are particularly sexy. Nor are they likely to have the kind of top-line impact (read: massive increases in revenue) that lead to promotions and bonuses. But they can save you a ton of pain and regret throughout the year. And without a doubt, they will make those revenue-spiking initiatives that much more successful.

Security Review

Having your domain blacklisted is nobody’s idea of fun. Because there’s no “Undo” button, once you’re in trouble, it’s time-consuming to get out. So, it is well worth reviewing your site’s security to ensure that no evil lurks in the heart of your coding.

Check your traffic logs and firewall settings to make sure you’re still keeping as much malicious activity off your site as possible.

If your site is custom coded, confirm with your developers that the code base is being updated regularly to guard against malware and other attacks. (Even fully customized sites generally rely on code libraries or frameworks that can be the target of attacks.)

If you use a commercial CMS, do a similar check with the vendor. It can be helpful to also do a web search for “[my CMS name] vulnerabilities” and other phrases to find reports of attacks.

An open-source CMS requires a similar review:

  • Do you have the most recent version installed?
  • Are all of the plugins, modules, widgets, and other helper programs up to date?

In all of these cases, you should be on a regularly scheduled maintenance plan with your development team. Now is the time to make sure you have the most appropriate level of protection.

Don’t forget the basics. A quick review is all that should be required to make sure that your registrar and hosting accounts are secure and your domain name and SSL certificate are in order and not at risk of cancellation. If you host internally, review server access to eliminate the chance of former employees making mischief.

Privacy Review

If GDPR and CCPA sound like alphabet soup to you, it’s definitely time to review your site’s privacy policy and things like data retention. This is now true even for non-transactional sites. GDPR may apply only to those of us who work with E.U. residents, but CCPA applies to most firms who interact with California residents. The Shield law applies to every firm in New York State.

That’s a lot to keep track of and understanding your responsibilities can be overwhelming. Given the potential fines involved, this is not an area where you want to take all of your advice from a marketer, coder, or (ahem) digital strategist. Be sure to have a knowledgeable lawyer review your privacy policies and practices.

Accessibility Review

Making websites accessible to people with disabilities is an area that has grown in importance over the past 18 months or so because of an increase in legal actions, even though the relevant regulations aren’t new.

The good news is that building new websites to be accessible isn’t particularly difficult, nor is maintaining that accessibility as new content is added. Both require an understanding of the requirements and a shift in approach.

The story is not quite as rosy for bringing existing sites into compliance, which tends to be more labor-intensive. Adjustments may include changes to branding and in-depth review of content (image alt tags, for example), as well as less visible coding changes.

There are a number of excellent assessment tools that can help you get an understanding of the effort required to make the site compliant. But a deeper, manual scan will also be required to uncover everything.

Analytics Review

Finally, don’t forget to review your analytics. This is one area that just may uncover insights that can lead to revenue growth that and a move closer to the corner office, though more likely those improvements will be incremental.

  • Compare statistics year-over-year to see where you’ve improved and where performance has fallen off.
  • Determine whether your mobile audience is growing or holding steady. (It’s probably not shrinking.)
  • Review traffic sources to see how visitors are finding you. That can guide adjustments to your marketing efforts.

You may be doing quite a bit of this on a monthly or quarterly basis as part of your marketing efforts. Still, it’s worth it to expand beyond that scope to look at broader performance and strive for continual improvement throughout 2020 and beyond.

How to Use Sentiment Analysis to Transform Your Digital Marketing Strategy

The goal of sentiment analysis is to increase customer acquisition, retention, and satisfaction. Moreover, it helps put the right brand messaging in front of the most interested eyes.

Sentiment analysis is a fascinating concept.

Brands use it to better understand customer reactions, behaviors, and opinions toward their products, services, reputation, and more. The goal of sentiment analysis is to increase customer acquisition, retention, and satisfaction. Moreover, it helps put the right brand messaging in front of the most interested eyes.

Before the digital age, gauging and understanding sentiment was an incredibly cumbersome process. It typically involved sending out surveys manually, going to the streets and asking people, or gathering focus groups in one place at one time. The big data-infused model of sentiment analysis we know today hit its stride on the political scene in 2010. Since then, it has morphed into a key tactic in marketing plans. These days, most of the grunt work is automated.

However, even with all of the advances in areas like martech, voice search, conversational commerce on social media, virtual assistants, and big data analytics, understanding how to actually use sentiment analysis to improve the bottom line is a complicated task.

Here are a few key approaches to help you get the value you need.

Know the Terms and Phrases That Indicate Intent

Most businesses today (hopefully) don’t even begin their digital branding and marketing efforts without a list of keywords relevant to their industry and a plan on how to target their audiences. You should have a good idea of the terms and variations that bring you traffic to your website, when used in conjunction with your brand and products. If you run an auto repair shop, people are likely finding you on the web through terms such as: body shop near me, auto repair, replace brake pads, etc.

Google Search Console gives you a great, fairly accurate idea of what’s bringing people to your website:

google search console
Credit: Author’s own

In terms of sentiment analysis, to gain actionable insight, you need to know how people are using these keywords in a way that indicates interest and engagement potential. Now, this is perhaps the biggest gray area in sentiment analysis, because not all positive sentiment equates to sales. Just because there are a lot of positive words around luxury cars doesn’t necessarily mean people are about to buy.

However, there are certain terms and phrases that signal people have entered your buyer’s journey. Let’s say you run an SEO agency and one of the terms you’re tracking for sentiment analysis is “Google update.” If you notice that a lot of people are searching for things like “what to do after a google algorithm update?” or “how to recover from a google penalty?” it’s a good indicator that they might need your services at the moment; you should target them accordingly.

Spot Patterns in Product Reviews

At its core, sentiment analysis is a game of pinpointing patterns and reading between the lines. Simply put, the more genuine and meaningful feedback you get on your product, the better insights you will gain into your customers.

Of course, gathering such high-quality feedback is easier planned than executed; especially for newer or smaller companies. Only 10% of customers will review or rate a business after a purchase, while half of consumers will leave a review only some of the time. However, the number of reviews jump significantly to 68% when a company asks the customer directly to leave one.

In order to find fruitful, up-to-date patterns, you need to make it a marketing process to consistently seek out new reviews. Then, you’ll want to start by searching for common adjectives. These should include words like:

  • great, simple, easy,
  • or awful, difficult, poor, etc.
trustpilot review
Credit: Capterra.com

In the above image, there are a good amount of reviews that include the word “great” for this product. Looking at the context around this term, we notice recurring patterns around components, like features and usability, and “not so” great opinions on customer service.

Finding recurring themes in customer sentiment will give you a better picture into the positive and negative aspects of your business or product. These can indicate the level of trust people have in your brand and how likely they are to give you a recommendation. When you are looking for patterns, try to come up with several adjectives that shed light on both sides of the spectrum.

  • What words are commonly used to describe their experience?
  • Is there an issue that forces multiple people to leave negative reviews?
  • What part delights them the most?
  • What’s preventing you from solving common problems?
  • Which products or solutions are users comparing yours to?

The answers to these important questions can help you understand user sentiment better and build a customer-focused marketing strategy.

Look to Social Media for Unabashed (Unfiltered) Opinions

Oftentimes, social media is one of the best places to get raw opinions, where people don’t hold back —  both in positive and negative lights. Knowing how people feel in an unfiltered environment can be a great way to tell which parts of your business are working very well —  and not so well.

A social listening platform is an important tool to keep in your portfolio for monitoring online mentions and gathering important datasets. Tools like Mention, Talkwalker, and Brand24, not only keep an ear on social mentions, but also turn these comments and hashtags into valuable customer analytics to help your marketing team understand your customers even better.

For instance, the online gaming developer Wargaming used brand monitoring techniques to analyze its customer’s desires and see which products performed best. The company tracked its users’ social media conversations to see what they were looking for, what parts of the games they liked or disliked, and any suggestions they offered for improvements.

Similarly, you can use a social listening tool to combine all your brand mentions into one database, giving your marketing team a bird’s eye view of audience sentiment on social platforms and identify areas to work on.

talkwalker
Credit: Talkwalker.com

While gathering this sentiment is good, the most important thing is knowing what to do with it. About 83% of customers who make a social mention of a brand —  specifically, a negative one —  expect a response within a day, and 18% want one immediately. Unfortunately, a majority of these mentions go unanswered, which can really impact a brand’s image. By utilizing an effective real-time social listening program, you can not only stay on top of social buzz, you can intervene and reply to any negative sentiment right away.

Some of the next steps will be fairly obvious, especially when you’re dealing with negative feedback. For instance, if your customer sentiment from social listening reveals that people are having trouble updating their software or there are issues with the product itself, this indicates that some redesign is necessary. However, don’t get too comfortable when you are getting positive reactions —  these tend to trick companies into thinking that no improvements are needed.

This kind of feedback can support a stronger marketing strategy. Let’s say your business sells pool supplies. While your customers may not be tweeting about your great chlorine chemicals, they are more likely talking about the fun pool floaties and games your website sells. Therefore, it would be helpful to highlight these fun accessories, as well, by listing them more prominently on your page and even including UGC to promote them.

poolfloatz
Credit: Instagram

Use Predictive Analysis to Spot Trends and Automate Actions

Now that you have all these valuable insights, you need to know how you can use them to shape your current and future business strategies.

Plugging your sentiment analysis into a predictive model is crucial for spotting trends, getting a feel for how opinions are progressing, and determining your next steps. Predictive analytics use machine learning and AI technology to not only gather, but analyze loads of consumer data and make accurate projections. These systems gauge historical behavioral data to help determine the best plan of action in the future.

In fact, customer segmentation and targeting (which is the logical next step after you analyze your audience’s sentiments) is one of the areas where applying AI and predictive analytics has the highest chance of working well for business.

applications of AI
Credit: Emerj.com

In order to develop an optimal predictive model for sentiment analysis, ask yourself:

  • What do you want to know?
  • What is the expected outcome? What do you think your customers are thinking?
  • What actions will you take to improve overall sentiment when you get the answers? How will you automate these actions?
  • What are the success metrics for these actions?

The Wrap

Chances are, your customers are already telling you what you need to make improvements to your business. By gathering as much data as possible on customer sentiment, your marketing team can understand just what needs to be done to provide a better experience, tweak campaigns accordingly, and acquire and retain more customers in the process.

Be sure you know what to data to collect, how to mine it, and how to apply it to keep raking in the revenue.

Why You Are Missing Out Without Conversion Tracking

Which digital marketing channels are driving the most leads and sales for your business? Are any channels just wasting your budget? Without properly set up conversion tracking, there’s no way to answer those two critical questions.

How can you tell if your new Google Ads campaign is improving your conversion rate? What percentage of visitors coming to your landing pages are there because of your Facebook Ads? You can’t get an accurate assessment of the ROI generated by your advertising efforts without implementing mechanisms to track visitor responses.

What Is Conversion Tracking?

Conversion tracking involves placing a piece of code on your website to track visitors and their actions. The data helps you understand their responses to various techniques used in your ad campaigns and different webpage designs. You can use conversion tracking for testing of keywords, redesigned landing pages, and new ad text.

Items You Should Be Tracking

  • Forms on your website (ex. quote requests, scheduled appointments, demo requests)
  • E-commerce sales
  • Coupon codes you give out as a way of encouraging people to visit physical locations
  • Phone calls

Here is what you gain by effectively tracking your digital marketing efforts.

1. Better ROI Tracking

You can add tracking codes to “Thank You” pages to monitor completed transactions by visitors and origination channels. That can tell you how many of those conversions came from visitors who clicked on specific advertisements. You can include tracking of signups, lead generation, or other items relevant to improving ROI.

2. Insights Into Campaign Successes

Some ads will perform better than others. Conversion tracking tells you how well specific keywords perform in attracting your target audience. You can also learn which ad campaigns to eliminate if they tend to draw visitors who quickly move away from your landing pages. Use information gained from your split testing efforts to tweak your keyword lists, ad copy, and landing pages for better performance.

3. Figuring Out What Content to Reuse

You want to stick with what works. Conversion tracking lets you know which content on your website attracted the most interest, or which campaigns helped drive higher-quality visitors. You want content that keeps visitors on your site who will eventually convert into a lead or sale.

4. Improved Audience Categorization

Segmenting audiences allows you to provide relevant content to those who visit your site or sign up to receive your email communications. Conversion tracking helps you figure out whether you have your contacts properly sorted for the type of information they receive.

Better categorization means your audiences aren’t sending your emails directly to the trash bin, or worse, clicking the “report spam” and/or “Unsubscribe” link. You also increase your chances of attracting the type of attention that leads to more conversions and better ROI.

5. Knowledge of Where to Direct Marketing Budget

Marketers running campaigns on a limited budget must maximize each dollar spent, while being cost-efficient. That allows you to create more effective campaigns that get the most for your money. You avoid dumping money into failing ad strategies and can direct those funds to higher-performing efforts.

Why Conversion Tracking?

Conversion tracking allows you to track and improve the ROI of your digital marketing campaigns by helping you identify your best-performing campaigns and eliminate those not delivering the desired conversion rates. It also helps you understand where you should be directing your budget across all the various marketing channels so you maximize every dollar invested.

Want more help tracking your marketing campaigns?  Click here to grab a copy of our “Ultimate Google Analytics Checklist.”

Striving for Continuous Website Marketing Improvement

Taking small actions on a regular basis are likely lead to more meaningful improvements to your website marketing than a large investment in a website “refresh” or relaunch every two or three years.

It’s a mistake to think about your website marketing efforts as set-it-and-forget-it investments.

You’re probably thinking, “Well, yeah. That’s pretty obvious!”

It’s unlikely that you aren’t aware of the value and importance of a steady stream of fresh content on your website at this point in the maturity of the web as a digital marketing tool. And you’re almost certainly already aware of the necessity to integrate your website into your marketing more broadly, from your email marketing to your social media efforts to your CRM system.

All of which means you have a pretty dynamic website. It doesn’t look the same today as it did six months ago.

But that’s not where your growth-focused thinking should end. If you seek to continually improve your marketing performance, you have to implement incremental changes to your website on a regular basis.

Finding the Right Frequency for Marketing-Focused Website Updates

How frequently you make these changes will depend on your site’s traffic volume and the resources you have to identify opportunities for improvement and to make the necessary changes .

Regardless of frequency, the key is to make changes systematically and track performance so you know what’s working and what isn’t.

The improvements you make should be based on three kinds of data:

  • Straightforward analytics metrics
  • Feedback from prospects, clients, your sales team, and other client-facing staff
  • Your gut

That last one is sure to be either a shock to your system or to make you sigh with relief. Even with data-driven marketing being all the rage — and justifiably so, in most situations — there’s no reason not to lean on your years of experience and what your inner voice is telling you.

For example, a client of ours didn’t have a lot of data to back up the changes she wanted to make to a section of her website that was neither outperforming nor lagging behind other content. She just had a hunch that changes would have an impact on engagement and lead generation.

We helped her update the presentation of this particular content in a way that made it more useful beyond the website, easier to connect to through her email marketing, and far more sharable on social media.

We also worked to update her analytics so that future updates in this areas could be based on metrics, as well any hunches the client had.

What Will Move the Marketing Needle?

Not sure what might move the needle? The best places to start include these:

  • Calls to action
  • Content gating strategies
  • Progressive profiling parameters
  • Page layout and design
    • Colors
    • Pull quotes
    • CTA placement

Changes to any one of these could yield measurable improvements in engagement or conversion rates. And taking small actions on a regular basis are likely lead to more meaningful website marketing improvements than a large investment in a website “refresh” or relaunch every two or three years.

Overall, the key to continuous improvement in your marketing is measurement. Experimentation and adjustment can easily become change for change’s sake, if you’re not measuring impact.

I would also caution against chasing after the latest shiny object. That’s a real danger, if you implement a policy of incremental changes without a long-term plan documented and agreed to by your entire team. Know where you want to go in the long-term and take short-term actions to move you closer to your digital marketing goals.

Viewability: How to Act on This Gift to Advertisers and Return to Advertising Transparency

Viewability and engagement signals provide advertisers with the right tools to measure ad effectiveness and to determine whether or not they’re spending their media dollars effectively. Two of the most powerful signals for determining effectiveness include viewability and, of course, engagement.

Smart advertisers need the right tools to measure ad effectiveness and to determine whether or not they spent their media dollars effectively. Two of the most powerful signals for determining effectiveness include viewability, which launched onto the digital scene in 2014 and, of course, engagement (clickthroughs, time-on-site, shares, likes, follows, etc.). But how should advertisers interpret and act on these signals? And when, if ever, do these metrics overlap with each other, when it comes to buying and optimizing media?

Depending on the advertiser’s objective with a given media initiative, the answers will become far clearer.

Determine Strategic Objectives

The fact is, engagement signals should be leveraged differently and at various times, based on overarching strategic objectives. For example, advertising initiatives designed to foster product or service evaluation may rely on clickthroughs and time-on-site as measurements of ad effectiveness, out of necessity. Because of the targeted nature of the initiative that aims to elicit a response, engagement signals make sense. Optimizing for high-engagement ads, while buying viewable impressions, will likely result in a more qualified audience … at a price that may, or may not, be worth it. The advertiser simply must decide what makes economic sense on a case-by-case basis.

If an advertiser wants to drive inspiration and consideration among potential customers, then getting in front of as many viewers with whom the advertiser’s product or service could resonate becomes the primary objective. In this case, engagement metrics may fall short, as would cost-per-thousand impressions (CPM) since an impression, whether viewable or not, gets factored into that calculation. Relying solely on CPM gives only a partial indication of the effectiveness of the ad spend and no indication of the ad effectiveness, whatsoever. Enter viewability.

The Importance of Measuring Viewability

While still an imperfect measurement of ad effectiveness, viewability gives advertisers the option of only paying for impressions that were, in fact, “viewable.” While there has been some ambiguity around what qualifies as “viewable,” the Interactive Advertising Bureau (IAB) and Media Rating Center (MRC) have made strides in standardizing the industry’s definition (opens as a PDF) of “viewable.” According to its definition, an ad is only viewable if “a minimum of 50% of the ad is rendered on a user’s browser for a minimum of one second for display ads and two seconds for video ads.”

This improved transparency and common benchmark is critical, in order to continue growing upper-funnel channels and tactics by restoring advertiser faith in the impressions reported. By differentiating between impressions-served and impressions-viewed, advertisers at least have the choice to optimize toward impressions-viewed (at a higher CPM) vs. the opaque alternative.

Viewability Tools for Publishers

Now, even Google’s instituted a “viewability” signal for publishers in its Ad Exchange called “Active View.” Accredited by the MRC, Active View measures impressions generated across publishers’ websites and apps in real-time. Because advertisers increasingly opt to buy viewable impressions, Active View provides publishers with the information they need to increase the value of their display inventory, over time. Publishers with the most viewable inventory will benefit from this buying trend.

Viewability Is Long Overdue

It’s safe to say that viewability is critical and long overdue. It does not, nor should it, devalue engagement metrics. Viewability and engagement metrics can be leveraged simultaneously or irrespectively. Again, it’s important to consider what the advertiser aims to achieve and understand the broader shift in transparency viewability offers.

In full disclosure, I was reared as a direct response marketer, so I am naturally inclined to lean on engagement signals as measurements of ad effectiveness. However, the reflex to solely rely on these metrics can be myopic. If you, too, classify yourself as a direct response marketer, performance marketer or any other flashy way to describe advertisers who care about the bottom line, then I challenge you to question what those lexicons really mean.

Be on the lookout for viewability buzz to continue gaining steam and momentum. This data signal offers much more than a simplistic measurement of ad effectiveness. It provides a return to advertising transparency that has been long under siege in the world of display. It’s a positive step and has its place in enhancing the way we think about buying media.

Nostalgic for the Future: Data That is ‘Close to You’

Last week, I had a dream — and in it, Karen Carpenter and I were friends. The following night, I had a similar dream — and this time it was Carly Simon. I literally went to bed the next night hoping for a Roberta Flack visitation.

Last week, I had a dream and in it, Karen Carpenter and I were friends. The following night, I had a similar dream and this time it was Carly Simon. I literally went to bed the next night hoping for a Roberta Flack visitation. As a result of these slumbering vocalists and songwriters, I’ve spent a good part of my leisure time over the New Year holiday listening to all their songs on my iPod. It’s yesterday, once more.

Who knows why we dream what we dream?

Sometimes, it just happens that when we’ve experienced enough in life, in play, in work some situations are bound to come around again, next week or decades later. I mean, I owned all that vinyl way back then and now I can stream it all again.

Greatest Hits: Lifecycles of Data-Inspired Marketing

So when Marc Pritchard of Procter & Gamble last week at the Consumer Electronics Show talked about “a world without ads,” I said to myself “oh, I’ve heard this song before.” And he’s right to say it.

In the world of data and direct marketing, a quest for wholly efficient advertising and a mythical 100-percent response rate actually is a 100-year science. Thank you, visionaries, such as Claude Hopkins.

• The 19th Century shopkeeper knew each customer, and conversed regularly. Ideally, each customer’s wants and desires were noted and needs anticipated to the extent that the customer was fulfilled accordingly. (Aaron Montgomery Ward and Richard Warren Sears.)
• Direct marketing originally through print, catalogs and mail, and then broadcast sought to replicate this model remotely. Measurement, attribution and response were put to science. Creativity served the science, or science served the creativity in either direction. Segmentation, analytics and differentiated communication flowed. (David Ogilvy, Stan Rapp and Alvin Eicoff, among others).
• In digital, social and mobile, direct marketing is rejuvenated this time “data-driven marketing.” Some have described this as data-inspired storytelling, or direct marketing on steroids. How responsible data collection can be used to identify prospect needs and wants, and funnel tailored communication through to sale, service and repeat purchase. (Jeff Bezos, among others.)
• And now the product itself can be designed to communicate to the customer smart appliances, smart cars, and the parts and products inside, with sensors and Internet connections and mobile app interfaces all being able to let the user know, it’s time for consideration or some other product lifecycle action.

Post-Advertising: A Reverence for Data

In all these examples, the constant is “I want to know you, so I can serve you the customer” and the facilitator is data. We exist to create and serve a customer. Period. Anything less is not sustainable. Data, in these models, is sought, analyzed and revered. It is also transparent, and its use and application has consumer buy-in. That premise is as true now in the Internet age, as it was in the direct response era before it. We all need to excel in data reverence, first, and then data analysis and application.

Advertising does have a role here, of course. Not every product sells itself and not every product meets customer satisfaction fully. The best advertising, and even the best data behind it, cannot save a bad product. There is always a need for advertising and marketing to inform the consumer, and a brand promise that serves to attract and retain beyond the product.

Every generation has its pop heroes. Tonight, I may just dream of Adele.

Factors for Marketers to Consider in Attribution Rules

At the end of each campaign effort, a good database marketer is supposed to study “what worked, and what didn’t,” using attribution rules. Call it “Back-end Analysis” or “Campaign Analytics.” Old-timers may use terms like “Match-back.” Regardless, it is one of the most important steps in 1:1 marketing that is synonymous with what we used to call “Closed-loop Marketing.”

At the end of each campaign effort, a good database marketer is supposed to study “what worked, and what didn’t,” using attribution rules. Call it “Back-end Analysis” or “Campaign Analytics.” Old-timers may use terms like “Match-back.” Regardless, it is one of the most important steps in 1:1 marketing that is synonymous with what we used to call “Closed-loop Marketing.” (refer to my first article on Target Marketing from 11 years ago, “Close the Loop Properly”).

In fact, this back-end analysis is so vital that if one skips this part of analytics, I can argue that the offending marketer ceases to be a 1:1 or database marketer. What good are all those databases and data collection mechanisms, if we don’t even examine campaign results? If we are not to learn from the past, how would we be able to improve results, even in the immediate future? Just wild guesses and gut feelings? I’ve said it many times, but let me say it again: Gut-feelings are overrated. Way more overrated than any cheesy buzzword that summarizes complex ideas into one or two catchy words.

Anyhow, when there were just a few dominant channels, it wasn’t so difficult to do it. For non-direct channel efforts, we may need some attribution modeling to assign credit for each channel. We may call that a “top-down” approach for attribution. For direct channels, where we would know precisely who received the offers, we would do a match-back (i.e., responders matched to the campaign list by personally identifiable information, such as name, address, email, etc.), and give credit to the effort that immediately preceded the response. We may call that a “bottom-up” method.

So far, not so bad. We may have some holes here and there, as collecting PII from all responders may not be feasible (especially in retail stores). But when there was just direct mailing as “the” direct channel, finding out what elements worked wasn’t very difficult. Lack of it was more of a commitment issue.

Sure, it may cost a little extra, and we had to allocate those “unknown” responders through some allocation rules, but backend analysis used to be a relatively straightforward process. Find matches between the mailing (or contact) list and the responders, append campaign information — through what we used to call “Source Code” — to each responder, and run reports by list source, segment, selection mechanism, creative, offer, drop date and other campaign attributes. If you were prudent to have no-mail control cells in the mix, then you could even measure live metrics against them. Then figure out what worked and what didn’t. Some mailers were very organized, and codified all important elements in those source codes “before” they dropped any campaigns.

Now we are living in a multi-channel environment, so things are much more complicated. Alas, allocating each of those coveted responses to “a” channel isn’t just technical work; it became a very sensitive political issue among channel managers. In the world where marketing organizations are divided by key marketing channels (as in, Email Division vs. Direct Mail Division), attribution became a matter of survival. Getting “more” credit for sales isn’t just a matter of scientific research, but a zero-sum game to many. But should it be?

Attribution Rules Should Give Credit Where Credit’s Due

I’ve seen some predominantly digital organizations giving credit to their own direct marketing division “after” all digital channels took all available credit first. That means the DM division must cover its expenses only with “incremental” sales (i.e., direct-mailing-only responses, which would be as rare as the Dodo bird in the age of email marketing). Granted that DM is a relatively more expensive channel than email, I wish lots of luck to those poor direct marketers to get a decent budget for next year. Or maybe they should look for new jobs when they lose that attribution battle?

Then again, I’ve seen totally opposite situations, too. In primarily direct marketing companies, catalog divisions would take all the credit for any buyer who ever received “a” catalog six months prior to the purchase, and only residual credit would go to digital channels.

Now, can we at least agree that either of these cases is far from ideal? When the game is rigged from the get-go, what is the point of all the backend analyses? Just a façade of being a “data-based” organization? That sounds more like a so-called “free” election in North Korea, where there are two ballot boxes visibly displayed in the middle of the room; one for the Communist Party of the Dear Leader, and another box for all others. Good luck making it back home if you put any ballot in the “wrong” box.

Attribution among different channels, in all fairness, is a game. And there is no “one” good way to do it, either. That means an organization can set up rules any way it wants them to be. And as a rule I, as a consultant, tend not to meddle with internal politics. Who am I to dictate what is the best attribution rule for each company anyway?

Here’s How I Set Up Attribution Rules

Now that I am a chief product guy for an automated CDP (Customer Data Platform) company, I got to think about the best practices for attribution in a different way. Basically, we had to decide what options we needed to provide to the users to make up attribution rules as they see fit. Of course, some will totally abuse such flexibility and rig the game. But we can at least “guide” the users to think about the attribution rules in more holistic ways.

Such consideration can only happen when all of the elements that marketers must consider are lined up in front of them. It becomes difficult to push through just one criterion — generally, for the benefit of “his” or “her” channel — when all factors are nicely displayed in a boardroom.

So allow me to share key factors that make up attribution rules. You may have some “A-ha” moments, but you may also have “What the … ” moments, too. But in the interest of guiding marketers to unbiased directions, here is the list:

Media Channel

This is an obvious one for “channel” attribution. Let’s list all channels employed by the organization, first.

  • Email
  • Direct Mail (or different types of DM, such as catalog, First Class mail, postcards, etc.)
  • Social Media (and specific subsets, such as Facebook, Instagram, etc.)
  • Display Ads
  • Referrals/Affiliates
  • Organic Search/Paid Search
  • Direct to Website (and/or search engines that led the buyers there)
  • General Media (or further broken down into TV, Radio, Print, Inserts, etc.)
  • Other Offline Promotions
  • Etc.

In case there are overlaps, which channel would take the credit first? Or, should “all” of the responsive channels “share” the credit somehow?

Credit Share

If the credit — in the form of conversions and dollars — is to be shared, how would we go about it?

  • Double Credit: All responsible channels (within the set duration by each channel) would get full credit
  • Equal Split: All contributing channels would get 1/N of the credit
  • Weighted Split: Credit divided by weight factors set by users (e.g., 50% DM, 30% EM, 20% General Media, etc.)

There is no absolutely fair way to do this, but someone in the leadership position should make some hard decisions. Personally, I like the first option, as each channel gets to be evaluated in pseudo-isolation mode. If there was no other channel in the mix, how would a direct marketing campaign, for example, have worked? Examine each channel and campaign this way, from the channel-centric point of view, to justify their existence in the full media mix.

Allocation Method

How will the credit be given out with all of those touch data from various tags? There are a few popular ways:

  • Last Touch: This is somewhat reasonable, but what about earlier touches that may have created the demand in the first place?
  • First Touch: We may go all of the way back to the first touch of the responder, but could that be irrelevant by the time of the purchase? Who cares about a Christmas catalog sent out in November for purchases made in May of the next year?
  • Direct Attribution: Or should we only count direct paths leading to conversions (i.e., traceable opens, clicks and conversions, on an individual level)? But that can be very limiting, as there will be many untraceable transactions, even in the digital world.
  • Stoppage: In the journey through open, click and conversion, do we only count conversions, or should the channel that led to opens and clicks get partial credit?

All of these are tricky decisions, but marketers should not just follow “what has been done so far” methods. As more channels are added to the mix, these methods should be reevaluated once in a while.

Time Duration (by Channel)

Some channels have longer sustaining power than others. A catalog kept in a household may lead to a purchase a few months later. Conversely, who would dig out a promotional email from three weeks ago? This credit duration also depends on the type of products in question. Products with long purchase cycles — such as automobiles, furniture, major appliances, etc. — would have more lasting effects in comparison to commodity or consumable items.

  • Email: 3-day, 7-day, 15-day, 30-day, etc.
  • Direct Mail — Catalog: 30-day, 60-day, 90-day, etc.
  • Direct Mail — Non-catalog: 7-day, 14-day, 30-day, 60-day, etc.
  • Social: 3-day, 7-day, 15-day, etc.
  • Direct Visit: No time limit necessary for direct landing on websites or retail stores.
  • General Media: Time limit would be set based on subchannels, depending on campaign duration.

Closing Thoughts

The bottom line is to be aware of response curves by each channel, and be reasonable. That extra 30-day credit period on the tail end may only give a channel manager a couple extra conversions after all of the political struggles.

There is really no “1” good way to combine all of these factors. These are just attribution factors to consider, and the guideline must be set by each organization, depending on its business model, product composition and, most importantly, channel usages (i.e., how much money bled into each channel?).

Nevertheless, in the interest of creating a “fair” ground for attributions, someone in a leadership position must set the priority on an organizational level. Otherwise, the outcome will always favor what are considered to be traditionally popular channels. If the status quo is the goal, then I would say skip all of the headaches and go home early. You may be rigging the system — knowingly or unknowingly — anyway, and there is no need to use a word like “attribution” in a situation like that.

3 Session Highlights for the 2018 FUSE Digital Marketing Summit: AI, Analytics, & How to Size Up Your MarTech Stack

The FUSE Digital Marketing Summit is quickly approaching. Subscribers to the FUSE Digital Marketing Newsletter should already have a sense of what we’ll be covering at the summit, but I just wanted to take a minute to highlight three key sessions that alone warrant marketers spending time attending the summit.

First, a little quick background on the summit:

Where & When: The FUSE Digital Marketing Summit will take place November 27 to 28 in Center City Philadelphia.

Why: With marketers constantly vetting, evaluating, and investing in new technology the two-day FUSE summit is designed to help marketers quickly identify and adopt the most relevant digital technologies. FUSE will dissect the modern martech stack and explore in-depth how the right technologies can enable marketers to achieve real business objectives.

Plus: FUSE Digital Marketing is a free, all-inclusive experience for qualified attendees — senior-level decision makers leading martech strategy and buying decisions. See if you qualify and learn more about the summit here.

Below are three general sessions attendees can look forward to. However, it’s worth noting the unique format of the FUSE summit – attendees will also participate in small-group boardroom case studies and have pre-scheduled 1-on-1 meetings with tech providers. And perhaps most valuable of all are the many networking opportunities with like-minded marketing executives.

3 Key Sessions at the 2018 FUSE Digital Marketing Summit

Keynote: Using AI & Deep Learning to Generate Marketing Results

In this eye-opening session, marketing AI practitioner and BrainTrust Insights co-founder Christopher Penn will explore how artificial intelligence and machine learning are changing marketing. Penn will cover what AI is – and isn’t – and what problems it’s good at solving versus the problems AI solves poorly. This session will use real-life marketing applications to illustrate how AI can elevate content marketing, lead targeting, conversion analysis, and business intelligence. And Penn will share his insight on what marketers need to do to prepare for an AI future.

Speaker: Christopher Penn, Co-Founder & Chief Innovator, BrainTrust Insights

How Do You Stack Up? Practical Advice for Constructing & Managing Your Marketing Tech Stack

In every industry, marketing technology stacks are growing in size and complexity as more products are deployed and integrated, and multiple teams throughout the organization embrace marketing technology in support of digital transformation initiatives. It’s not unusual to see companies using more than 100 different marketing tools at any one time. With a need to integrate many of those tools, building and managing the marketing technology stack has become a tremendous challenge for many organizations.

Leveraging the insights gleaned from hundreds of marketing technology stacks, this session will cover the technologies that companies are currently buying, and the hot technologies that they are looking to integrate into their stack.

Speaker: Anita Brearton, Founder & CEO, CabinetM

How the American Medical Association is Using Analytics to Grow Membership

Content marketing, digital marketing, and consumer marketing have converged to transform how organizations can interact with customers. As a digital change-agent for the past 20 years, Todd Unger, CXO of the American Medical Association, will show how he is transforming AMA’s marketing, using analytics tools to generate insights, quantify content marketing ROI and boost member acquisition and retention efforts.

Speaker: Todd Unger, Chief Experience Officer/SVP Physician Engagement, American Medical Association

Check out the full summit agenda here.