The Role of Marketing in the All-Digital World

How demand generation strategies have pivoted during these challenging times.

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Marketers exist to create demand and that is not easy in the current situation. As many tactics, channels and budgets are all changing, many of us are facing the greatest challenge of our careers. Especially for small and growing businesses, marketing is the tip of the sphere for growth. How do we make ourselves relevant during a period of uncertainty?

Join Meghan Gendelman, VP of Marketing at Salesforce and Dr. Ann Marie Sastry, CEO of Amesite for a special webinar on how to make your marketing relevant in the all-digital, work-from-anywhere world.

Don’t miss this webinar! Register today for “The Role of Marketing in the All-Digital World,” presented by Salesforce.

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CCPA enforcement starts now and most companies aren’t ready

Unprepared for CCPA? Here is what you need to know and do — now.

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The California Consumer Privacy Act (CCPA) went into effect on January 1, 2020 with a six-month enforcement grace period. That end date is now here.

The basics. As a refresher, CCPA explicitly applies to companies that qualify under one or more of the following statutory criteria:  

  • Have gross annual revenues in excess of $25 million;
  • Possess the personal information of 50,000 or more consumers, households, or devices; or
  • Earn more than half of their annual revenue from selling consumers’ personal information

A number of categories of businesses are explicitly exempted from CCPA compliance, including certain industries covered by federal regulations. However, most publishers will need to be ready to enable U.S. consumers to opt-out of third-party data transfers and demonstrate compliance to regulators in the event of an investigation or complaint.

Attorney Aaron Tantleff, a partner at law firm Foley & Lardner, offers a sliver of hope that CCPA may not apply to everyone, while cautioning that the law has few geographic boundaries. “We have spoken with many clients that have called in a panic to discover that CCPA does not apply. The applicability of the CCPA, like the GDPR, is not limited to only those organizations based in California. It may apply to organizations that lack any physical presence in the State.”

Broad application to businesses globally. As a practical matter the statute will broadly apply to most commercial enterprises, whether or not they explicitly target California residents.  For example, an early analysis of the legislation by the IAPP says:

Companies may pass [the personal information of 50,000 consumers] threshold more quickly than anticipated because the scope of personal information is broad. Most companies operate websites and inevitably capture IP addresses. Notably, companies need to comply regardless of whether the website targeted businesses or individual customers in California given that the term “consumer” is defined to mean any “resident.” Even individual bloggers and relatively small businesses outside California may find it difficult to ensure that they do not receive personal information of more than 50,000 California resident visitors to their website annually, simply from having it be passively accessible from there, and, within California, most retailers, fitness studios, music venues and other businesses will meet this threshold.

Risks of non-compliance. The California Attorney general can impose financial penalties up to $2,500 for non-willful violations and $7,500 for intentional violations. But these numbers can multiple quickly if thousands or millions of users are implicated. In most cases there will be no liability where the violation is “cured” within 30 days of receiving notice. There is also a private or individual right of action when personal information is wrongfully disclosed under CCPA. (The first CCPA class action lawsuit [.pdf] was filed in February against Hanna Andersson and Salesforce.)

According a recent Ethyca survey of 218 general counsels of technology companies, 56% said they were “unprepared for new privacy regulations coming in around the globe,” which includes CCPA. During the months leading up to the enforcement deadline, 43% of respondents said they had deprioritized privacy preparedness because of COVID-19. The survey also found that lack of resources or cost was the greatest challenge in complying.

What to do now. “For businesses still looking to button up on compliance, the essential — and only — first step is to figure out the personal data you possess and where it lives,” says Cillian Kieran, CEO of Ethyca. “After you’ve built a data map that has a thorough and complete record of the data you hold, and where it lives, you can worry about putting the structures in place to address various compliance tasks. But it all starts with the map.”

Attorney Tantleff adds, “Document everything. By now, organizations should have a robust set of security measures in place. However, under the CCPA, an organization must demonstrate that it has implemented reasonable security measures designed to protect personal information based upon the nature and sensitivity of that information.”

According to Lisa Rapp, VP of Data Ethics at LiveRamp, “No company should try to do this on their own. The best thing to do is to obtain as much information as possible by reading what industry leaders are saying, staying up-to-date on the materials that groups like the IAPP and IAB are putting out, and reaching out to prominent law firms that deal with data privacy to gain their legal counsel and interpretations of the law.”

Julie Rubash, VP of Legal at Nativo, recommends that publishers read the Attorney General’s final regulations “to ensure that current [privacy] plans are in line with the Attorney General’s interpretation.” She adds that “Tools like the IAB CCPA Framework are a step in the right direction to prepare for an inquiry and limit revenue disruptions. Publishers that leverage the IAB CCPA Compliance Framework tool and sign the limited service provider agreement are unlikely to experience a significant impact to their business models.”

Abby Matchett, Enterprise Analytics Lead at Bounteous, says, “Because CCPA takes a much broader view of personal data than Europe’s GDPR guidelines, most companies must undertake a significant internal inventory of any data that may be linked, directly or indirectly, with a consumer or household. Conducting such an inventory places a heavy burden on IT organizations, legal departments, and data analysts who may already be dedicated to other internal priorities. Overcoming this obstacle is one of the first steps towards compliance but is often the most challenging to coordinate and fully document.”

Matchett further explains, “If you are concerned that you may not have time to build a home-grown digital solution for this purpose, consider reaching out to third-party Cookie Consent Manager software companies that specialize in maintaining CCPA & GDPR ready solutions. Some common Consent Managers include TrustArc, OneTrust, and Quantcast, among others.”

Here comes CPRA. Even as many companies are struggling to comply with CCPA, a new November California ballot initiative could impose even tougher privacy rules if passed. According to the Future of Privacy Forum’s Katelyn Ringrose, “While companies may have begun, and in some cases, finalized strong compliance programs and efforts addressing the CCPA—the California Privacy Rights Act (CPRA), recently certified for the 2020 ballot, could have an enactment date as early as 2023, placing additional obligations on covered entities. The CPRA would create a sensitive data classification, place additional obligations on processors, and require the establishment of a California Privacy Protection Agency.”

Why we care. Large numbers of consumers have expressed concerns about how their data are being handled online. But there’s evidence that “privacy forward” companies are seeing both brand and financial benefits, in terms of greater consumer trust and even stronger revenue growth.

It’s foolish to delay taking the necessary steps to prioritize privacy and data security. As Tom O’Regan, CEO of Madison Logic put it, “Ultimately, complying with the CCPA controls will be far less expensive than penalties from non-compliance.”

Thursday’s Live with Search Engine Land will be a special CCPA and privacy discussion featuring Lisa Rapp, VP Data Ethics, LiveRamp, Abby Matchett, Enterprise Analytics Lead, Bounteous, Katelyn Ringrose, attorney, Future of Privacy Forum.

It starts at 1:00 p.m. EDT and will allow up to 100 people into the meeting to experience the discussion live and ask questions. If you’re a digital marketer you can’t afford to miss this. Sign up here.

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Analytics Audit 101: Identify issues and correct them to ensure the integrity of your data

Marketing and analytics professionals need to work together to not only increase the accuracy of our data, but to educate people about how to leverage it.

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One thing online businesses need to use as a cornerstone of their business decision making  process is their digital analytics data (analytics data from a variety of sources: i.e. web analytics, search console, paid search, paid social, social media, etc.). Yet, according to a MIT Sloan Management Review only 15% of more than 2,400 business people surveyed trust their data. While there is no analytics method available that will guarantee 100% accuracy of your digital analytics data, by auditing your data you can ensure the data is as accurate as possible. This will provide you with the confidence to not only trust your data but to leverage the information provided in making objective business decisions, instead of subjective decisions. It is that lack of trust that explains why a mere 43% (according to the same survey) say “they frequently can leverage the data they need to make decisions.” This low confidence in one’s data equals failure.

As marketing and analytics professionals, we need to work together to not only increase the accuracy of our data, but to educate people about the data and how to leverage it. The first step in this process is auditing your analytics configurations and thereby identifying issues, and correcting them to ensure the integrity of the data. 

The analytics audit process

Step 1: Acknowledge analytics data isn’t perfect

When you start your analytics process gather together all those who have a stake in the outcome and find out why they don’t trust the data. Most likely they have good reasons. Don’t make claims that your goals is to make it 100% accurate because that is impossible. Use the opportunity to explain at a high level that analytics data captures a sampling of user activity and for various technical reasons, no system will be perfect and that’s why they are most likely seeing data difference between things like their Adwords account and their web analytics data. Use an example of taking a poll. Pollsters take a sample ranging in size of 1,000-2,000 people of a total population of over 350,000 in the USA and then state their data is accurate within a few percentage points 4 out of 5 times. In other words, they are way off 20% of the time.  However, businesses, politicians and the general public respond and trust this data. When it comes to web analytic data even at the low end of accuracy, your data is likely still capturing an 80% sample which is far more accurate then the data presented by pollsters, yet it is less trusted. Let the stakeholders know, as a result of the audit and implementing fixes, you could be improving data capture accuracy to 90% or even 95%, and that is data you can trust 100%.

Step 2: Identify what needs to be measured

One of the biggest issues when it comes to analytics data is, the analytics software isn’t configured to collect only the correct data. The software becomes a general catch-all. While on the surface it sounds perfect to just capture everything (all that you can), when you cast a huge net you also capture a lot of garbage. The best way to ensure the right data is being captured and reported on is to review the current marketing and measurement plans. Sadly, too few organizations don’t have these, so during your meeting, make sure to ask what the stakeholders’ primary items they want measured are.

Identify and gather all the “Key Performance Indicators” (KPI) currently being reported on. You’ll need this before you start the audit. Verify all KPI are still valuable to your organization and not just legacy bits of data that have been reported for years. Sadly in many organizations, they are still reporting on KPIs that actually hold little to no value to anyone within the organization.

Step 3: Review the current analytics configuration

Now is the time to roll-up those sleeves and get dirty. You’ll need admin level access (where possible) to everything or at a minimum full view rights. Next you’ll need a spreadsheet which lists the specific items that you need to review and ensure are configured correctly and if not, a place to note what is wrong and a column to set a priority to get them fix.

The spreadsheet I’ve developed over the years has over 100 standard individual items to review, grouped into specific aspects of a digital analytics implantation plus depending on the specific client additional items may be added. The following eight are some of most critical items that need to be address.

  1. Overall Analytics Integrity: is your analytics code (or tag manager code) correctly installed on all pages of your website? Check and make sure your analytics code is correctly deployed. Far too often the javascript (or the code snippet) is located in the wrong place on the web page or perhaps it is missing some custom configuration. Simply placing the code in the wrong place can cause some data to not be captured.

    Verify the code is on all pages/screens. Too often either section of a site are missed or the code doesn’t work the same on all pages resulting in lost data or potentially double counting.

    If you run both a website and an app, are their analytics data properly synced for data integration, or is it best to run them independently?
  2. Security: Review who has access to the analytics configuration and determine when the last time an individual’s access and rights were reviewed. You’d be surprised how many times, it has been discovered that former employees still have admin access. This should be something that is reviewed regularly, plus a system has to be in place to notify the analytics manager when an employee departs an organization to terminate their access. While you may think since you’re using the former employee’s email address all is fine because HR will cancel that email address, they may still have access. Many analytics systems do not operate within your corporate environment and are cloud-based. As long as that former employee remembers their email address and the password to that specific analytics account they’ll have access.
  3. Analytics Data Views: This is an especially critical feature when it comes to web analytics (i.e. Google Analytics, Adobe Analytics, etc.). Is your analytics system configuring to segregate your data into at least 3 different views? At a minimum, you need “All Data” (no filtering), “Test” (including only analytics test data or website testing) and “Production” (only customer-generated data). In many organizations, they also segment their data further into “Internal Traffic” (staff using the website) and “External Traffic” (primarily external users).

    If these don’t exist, then it is likely you are collecting and reporting on test traffic and internal users. How you’re employees use a website is completely different than customers and should at a minimum be excluded or segmented into their own data set.
  4. Review Filters: Filters are a common tool used in analytics to exclude or include specific types of activity. Most filters don’t need to be reviewed too often, but some do need to be reviewed more frequently. The ones that need to be reviewed most often are ones that include or exclude data based on a user IP address. IP addresses do have a nasty habit of changing over time. For example, a branch location switched ISPs and received a new IP address. When it comes to IP based filters it is recommended they be reviewed every 6 months, but if not possible at least once per year. As a tip, after they’ve been reviewed and verified, rename the filter by adding the date they were last reviewed.

    Don’t forget to ensure that exclude filters are in place to exclude search engine bots and any 3rd party utilities used to monitor a website. This machine-generated traffic has a nasty habit, of getting picked up and reported on which skews all the data.
  5. Personally Identifiable Information (PII): Too many developers have a nasty habit of passing PII via the data layer especially on ecommerce sites. They are unaware that it is possible that this data can end in the company’s analytics database. By storing PII on a 3rd party system, you either need to reference this in your privacy policy and even then you might be breach of various privacy laws. One of the most common types of these errors is passing a users email address as a URI parameter. The easiest way to check for this is to run a pages report for any URI containing a “@” symbol. Over the years, I’ve seen customer’s names capture and much more.

    If this happens, ideally your developers should fix what is causing this, but at a minimum you’ll need a filter to strip this type of information from the URI before it is stored in your analytics database.
  6. E-commerce Data: This is the most common issue we hear from organizations: “The sales figures reported in the analytics doesn’t match our e-commerce system!” As stated above, analytics isn’t perfect nor should it be treated as a replacement for an e-commerce/accounting backend. However, if you are capturing 85-95% (and possibly higher) of the transactional data then you can effectively leverage this data to evaluate marketing efforts, sales programs, AB tests, etc.

    From an e-commerce perspective, the easiest way to audit this is to compare the reported data in a given time period to what the backend system reports. If it is near 90%, then don’t worry about it. If it is below 80%, you have an issue. If it is somewhere in between, then it is a minor issue that should be looked into but is not a high priority.
  7. Is everything that needs to be tracked being tracked: What does your organization deem important? If your goal is to make the phones ring, then you need to be tracking clicks on embedded phone numbers. If your goal is forms driven submissions, are you tracking form submissions correctly? If you’re trying to direct people to local locations, then are you capturing clicks on location listings, on embed maps, etc.?

    What about all those social media icons scattered on your website to drive people to your corporate Twitter, LinkedIn, Facebook accounts? Are you tracking clicks on those?
  8. Campaigns: Is there a formal process in place to ensure links on digital campaigns are created in a consistent manner? As part of this are your marketing channels correctly configured within your analytics system?

You now have an outline for where to start your analytics audit. Think of your organization’s analytics data and reporting systems like a car. It always seems to be working fine until it stops working. You need to take your car in from time to time for a tune-up. This is what an analytics audit is. The audit will identify things that need to be fixed immediately (some small and some big) plus other items that can be fixed over time. If you don’t fix the items discovered during the audit your analytics system won’t operate optimally and people won’t want to use it. How frequently should an analytics audit be conducted after everything has been fixed? Unlike a car, there is no recommended set amount of time between audits. However, every time your digital properties undergo major updates or if there have been a series of minor updates that can easily be viewed together as a major update, it is time to repeat the audit process.

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Soapbox: Is my data telling me the truth?

How email security programs affected my perception of data integrity.

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As marketers, we face the overwhelming challenge of demonstrating proof that our tactics are effective. But how can we convince management if we are not convinced of our own data?

Here’s the reality, which I recently learned for myself: If you’re running email marketing, it’s very likely that your performance reports are not disclosing the full truth… inflated CTRs (click-through rates) and open rates being the main culprits. 

Email security programs – loved by recipients, hated by senders

Barracuda. SpamTitan. Mimecast. Email bots that serve a single purpose: to protect users from unsafe content. These programs scan inbound emails and attachments for possible threats, including viruses, malware, or spammy content by clicking on links to test for unsafe content.

For email marketers, this creates several challenges:

  • Inflated CTRs and open rates due to artificial clicks and opens 
  • Disrupting the sales team’s lead followup process as a result of false signals
  • Losing confidence in data quality (quantity ≠ quality)

Real or artificial clicks?

In reviewing recent email marketing performance reports, I noticed an unusual pattern: Some leads were clicking on every link in the email…header, main body, footer, even the subscription preferences link — yet they were not unsubscribing. Not only that, but this suspicious click activity was happening almost immediately after the email was deployed. I speculated that these clicks were not “human”, but rather “artificial” clicks generated from email filters. 

Hidden pixels are your frenemy

To test my hypothesis, I implemented a hidden 1×1 pixel in the header, main body, and footer section in the next email. The pixels were linked and tagged with UTM tracking — and only visible to bots.

Sure enough, several email addresses were flagged as clicking on the hidden pixels.

All that brings me back to the question of whether or not marketing data can be trusted. It’s critical to “trust, but verify” all data points before jumping to conclusions. Scrutinizing performance reports and flagging unusual activity or patterns helps. Don’t do an injustice to yourself and your company by sharing results that they want (or think they want) to hear. Troubleshoot artificial activity and decide on a plan of action:

  • Use common sense and always verify key data points
  • Within your email programs, identify and exclude bots from future mailings
  • Share results with management, sales, and other stakeholders

A word of caution… 

Tread carefully before you start implementing hidden pixels across your email templates. Hiding links might appear to email security programs as an attempt to conceal bad links. You could be flagged as a bad sender, so be sure to run your email through deliverability tools to check that your sender score isn’t affected.

As the saying goes, “There are three kinds of lies: lies, damned lies, and statistics.” Sigh.

With different solutions circulating within the email marketing community, this is likely the “best solution out of the bad ones”. It all depends on what works best with your scenario and business model. 

Godspeed, marketer! 

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The Cost of a Bad Lead in 2020–The Demand Marketers Guide

Many marketers and senior leaders are unaware of the hidden costs and negative impact bad leads have on their business and revenue-generation efforts.

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Over the past few years, demand marketers have been inundated with advice on the quality over quantity debate, particularly when it comes to lead generation. By now, you know that 100 good leads are better than 300 dead leads.

So why do expensive and time-intensive demand programs and campaigns still deliver bad leads that miss the mark?

First, because demand marketers are under pressure to hit KPIs and targets, often within tight time frames, so accepting marginal leads is a reality. Secondly, because a large majority of the leads are generated via a third party at events, through paid media programs such as content syndication and social media. These inherently can be captured with out- of date information, inaccurate contact data and/or non-compliant opt-in.

Unfortunately, many marketers and senior leaders are still unaware of the hidden costs and negative impact bad leads have on their business and revenue-generation efforts. That’s why Integrate pulled together this guide to help you squash the marketing bad data problem. In this guide, they explore:

  • What is a good lead
  • What makes a lead bad
  • How to calculate the costs of a bad lead
  • What are the hidden costs of bad leads

Visit Digital Marketing Depot to download “Cost of a Bad Lead in 2020–The Demand Marketers Guide.

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How You Drive Revenue While Staying True to Your Brand Purpose

Leverage identity marketing to drive engagement with audiences resulting in revenue and enhanced brand trust.

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Building relationships with customers not only drives revenue but enhances brand equity. Developing a strategy that looks beyond transactional data to create unique customer experiences is paramount for today’s B2C brands.

Join Lino Reveles Trujillo from Headspace and Sai Koppala, the CMO from SheerID as they discuss how to implement strategies that move beyond basic attributes to build meaningful and personalized campaigns for customers.

Learn how to build personalization using a holistic approach that is more than just transactional data. Register today for “How You Drive Revenue While Staying True to Your Brand Purpose,” presented by SheerID.

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Call analytics platforms: What are they good for?

Use cases for call analytics platforms are expanding and AI is driving more sophisticated approaches.

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Marketers are using call analytics platforms to identify the rich data and consumer insights hidden in the growing volume of inbound calls. Call analytics platforms are one of the few martech systems that can track both online and offline leads. Call tracking – following a call from source (i.e., website, click-to-call search or display ad) to sales representative (i.e., based on geographic location or product line) – has been a core use case.

However, call analytics platforms now work for a number of marketing use cases, including the following:

  • Marketing attribution: Call analytics provide flexible attribution across media channels, helping brands understand which digital media are driving phone calls. PPC marketers, in particular, have adopted call analytics to connect callers to specific campaigns and keywords, and track keywords to conversion events. The goal is to optimize bids for the keywords driving the most productive calls.
  • Personalization: Call data can be combined with other martech system data to improve marketing personalization. Call analytics surface demographic data, product interest, buying stage and customer type. By pushing caller audiences into PPC, CRM or other marketing automation systems, marketers can optimize for the next right action.
  • Persona and lookalike audience building: Call analytics platforms record and transcribe calls, then apply AI-based models to the results to determine the characteristics of the highest-performing callers or leads. Marketers can then build personas or lookalike audiences to use in campaign development and execution.
  • Retargeting: Call recordings and transcriptions can also be used to retarget prospects based on the content – and insights derived – from their prior calls.
  • Sales enablement: Call analytics platforms can score calls based on transcript analysis, to identify which callers merit callbacks, evaluate agent performance and learn which scripts or offers work best.

Many of these marketing applications are being fueled by vendor investments in artificial intelligence (AI) and machine learning, which are driving greater speed and accuracy into caller insights. Call analytics technology is evolving from providing basic analytics to providing “conversational intelligence” based on highly sophisticated algorithms that can extract and predict caller intent, and measure caller tone, sentiment and emotion. The goal is to enable brand marketers to increase marketing effectiveness and sales conversions.

Marketing apps emerge for new technologies

New AI-driven technologies, including intelligent voice assistants, chatbots and messaging apps may also have a positive impact on the volume of mobile calls to businesses, although industry experts are still debating the marketing value of those calls. Nearly a quarter of U.S. adults (24%) own a smart speaker in 2020 — representing more than 60 million people, according to The Smart Audio Report, published by NPR and Edison Research. The report also found that the number of smart speakers in U.S. households surpassed 118 million in 2018.

And it appears those smart speakers and voice assistants are being used to connect with businesses, with many respondents saying they’d ordered food within the last week using their smart speaker (18%) or the voice assistant on their phone (24%). Additionally, seeking information about local businesses is a regular activity, with 31% of people reporting using their smart speaker for the purpose in the last week and 38% of respondents using the assistant on their phone.

Call data governance remains a priority

But even as brand marketers gain greater access and insight into individual consumer intent, call data privacy continues to be a priority, particularly for brands in the healthcare and financial services markets. Call analytics platform vendors must comply with Health Insurance Portability and Accountability (HIPAA) and Health Information Technology for Economic and Clinical Health (HITECH) regulations.

Many vendors automatically redact personally identifiable information (PII) and consumer financial information from call recordings and transcripts to comply with the Payment Card Industry Data Security Standards (PCI DSS), a set of security standards designed to ensure that companies that accept, process, store or transmit credit card information maintain a secure environment.

Several vendors use security measures such as data encryption and two-factor authentication. Others invest in third-party data security audits through organizations such as TrustArc (formerly TRUSTe), a technology compliance and security company.

The European Union’s (EU) General Data Protection Regulation (GDPR) went into effect in May 2018 and impacts all U.S. marketers and data firms handling European data or serving customers in the EU. In June 2018, California legislators passed the California Consumer Privacy Act of 2018, which grants consumers more control over the use of their personal information online. The law went into effect in January 2020, and defines personal information as anything that can be associated or linked with an individual or household.

These regulations are driving an expanded industry focus on data governance, with a view toward complying with new standards for the benefit of consumers, as well as marketers.

If these benefits sound like what you’re looking for, check out our Martech Intelligence Report for in-depth info on the call analytics space and in-depth profiles of vendors.

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Are you using the optimal mix of marketing channels?

Maximize your campaign response rates and ROI with insights from nearly 600 multichannel marketers.

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Most marketers rely on more than one channel to achieve the best possible results from their campaigns. However, new research from PFL and Demand Metric reveals that marketers are not consistently using the most effective channels and multichannel strategies.

PFL partnered with Demand Metric to uncover the most effective multichannel marketing strategies and share these insights and benchmarks with you so you can maximize your ROI. Download this benchmark report and learn:

  • The top 3 most effective channels for reaching your target audience.
  • The top 5 multichannel campaign ROI success factors in 2019.
  • The top 4 channels and cadences for influencing the C-Suite.

Visit Digital Marketing Depot to download “Multi-Channel Marketing – Maximizing Program Engagement and ROI.

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Why marketers need identity to build consumer trust in a cookieless world

Marketers must have the right walled garden and publisher relationships, linked to a strong identity foundation, in order to establish and sustain trusted consumer relationships.

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For years, cookies were the connective links that helped marketers understand and reach consumers, but no more. Navigating this uncharted terrain is doable though. The keys to success are privacy-friendly, identifiable connections and relationships with those who have them.

Lots of factors have forced marketers to look beyond the cookie – from consumer privacy demands and California’s sweeping privacy law to the rise of so-called walled gardens and an increasingly fragmented media landscape.

That cookies are losing their usefulness is no surprise to anyone. Yet, with cookies going the way of the dodo, marketers need new ways to identify consumers and measure marketing performance. That means they’ll need to make a big shift away from the old-school audience targeting they’ve known.

Now more than ever marketers will need It to invest in first- and second-party data to augment the insights they once got from third-party cookies. To do that, they’ll need to partner with publishers and content producers who already have the right consumer relationships to sustain effective, personalized marketing. And they’ll need to make the value exchange clear to consumers.

Behind walled gardens, marketers need identity for holistic brand messages

For marketers, the importance of managing consumer identity is nothing new. As early as 2016, Forrester said, “it’s becoming more critical than ever for firms planning to link systems of insight and engagement to foster seamless and relevant cross-channel customer experiences.” They understood that marketers need new ways to create smooth interactions across multiple touchpoints with people – not cookies.

In many ways, consumer demand for better privacy safeguards led us toward our identity-centric marketing landscape. People wanted more control over which brands have access to their data and for what purposes. The California Consumer Privacy Act of 2018 compelled marketers to give them that control. As a result, consumer data will no longer float around through third-party cookies in the near future. Consumers can choose whether to give brands access to information through a more fair value exchange.

Consumer identity is at the core of how brands can manage this value exchange with people. If you follow the money, you’ll see this is already playing out. Just look where advertising budgets are gravitating. Right now more than 70% of digital ad dollars flow to places with direct links to identifiable consumers, not cookies.

Many of those interactions with identified consumers take place behind the walled gardens of the three digital ad revenue leaders – Amazon, Facebook and Google. Why? Despite their privacy difficulties, overall, these brands have done a good job of developing trust with consumers. After all, people still use Google every day for convenient services. And they’re still on Facebook and its subsidiary Instagram. In fact, eMarketer data shows time spent on Facebook, Instagram, and Snapchat is on the rise as people connect with friends and loved ones during the pandemic.

The value exchange is clear: these giants provide content and services consumers not only want, but they rely on. So, in exchange, people are willing to give them access to identifiable information like emails or phone numbers as well as interest-based clues that help those platforms sustain and grow those relationships through customized offerings.

As they have built relationships with consumers, Amazon, Facebook and Google have grown their consumer identity gardens. They possess troves of authenticated consumer identity data, so as a result, they’ve limited the effectiveness of third-party cookies on their platforms. It makes sense; they just don’t need them. They’ve gained and maintained dominance, in part by making it a challenge to access that precious consumer identity.

Increased use of mobile devices, where cookies were unreliable if not entirely inoperable, also contributed to this shift. But as third-party cookies become obsolete, marketers still need to create seamless, personalized interactions with consumers across multiple touchpoints. So, they need to access the identifiable consumer data that’s behind those walls. That means either partnering with the walled gardens or with entities that already have those relationships.

This is imperative for marketers who want to reach consumers with a cohesive message no matter where they are, and gauge campaign effectiveness. For instance, without a holistic view enabled through identity infrastructure across channels, marketers would not be able to engage with the same customer on their work and home computers. They would not be able to make direct mail offers reflecting online purchases. And they would not be able to tie their marketing efforts back to measurable insights generated by ad servers, DSPs, platforms and publishers.

How identity partnerships creates better privacy and customer experience

As marketers trek through an advertising environment without cookies, a privacy-safe consumer identity approach is super important. A recent report from Winterberry said that marketers should “prepare for a potential cookie-less future and monitor the role of Mobile Advertising IDs and other Personal Identifiers.” Part of that process, suggested the report, should involve integrating “privacy as a (non-exclusive) marketing discipline” throughout an organization.

Some may think the idea of consumer identity is at odds with privacy. But it’s not at all. In fact, consumer identity protects consumer privacy because it connects marketers only to the information they need to know about a consumer in order to provide a relevant, trustworthy experience. Partnerships that link marketers to consumer identity held by publishers, platforms and other content producers can help reinforce trusting bonds between people and brands.

A PwC study found 65% of customers said a positive experience with a brand is more influential than great advertising. That’s saying a lot. Good experiences with brands happen when they are privacy-safe, relevant and customized in a way a consumer sees as fitting for the relationship. Positive interactions between consumers and brands help to generate first-party data by generating trust. It’s the basis for what Forrester calls an “identity backbone.”

Here’s a timely illustration of what I mean. A lot of us sheltering-in-place right now are looking around at the same four walls, tempted to change what we see. Let’s say you’ve got the home renovation bug. You’re thinking about knocking down a wall, and your partner would love to change the paint colors in the kids’ rooms.

With so much time at home, you decide to do the DIY thing. So, you visit your local hardware store to pick up some supplies. Because you’re the one who made the purchase and there’s no reason for the hardware retailer to know you’re married with kids, the store doesn’t have data revealing that.

The store does, however, know what it needs to know: the items you bought. As a regular customer you’re a loyalty program member, so you’ve provided your email and address already, and you got loyalty points with your purchase. To most consumers this is a clear and worthy value exchange. It’s even more valuable when you receive an email with a 10% discount on your next purchase.

Identity resolution makes this possible. Consumers are comfortable with it because they appreciate the way it makes their lives easier and improves a relationship with a brand they actually choose to engage with. But identity becomes even more valuable for them when it is used to ensure walled gardens and brands only get the information consumers want them to see.

Let’s say your partner decides that rather than just knocking out a wall, you should add an expansion to the back of the house. Quarantine can have this effect on people! He goes online to check out home loan rates. You have a joint checking account, so the bank does know you are married. You have a 529 college savings account for the kids, too. As your financial services provider, its relevant data it makes sense for them to know.

Either one of those brands might want to reach you with an offer based on those interactions on a walled garden platform like Facebook, for example. In this case, having a trusted and privacy-safe connection point that links brands to consumer identity ensures that the hardware store, the bank or the walled garden each sees only what you have given permission for them to see.

Put simply, while you know your own complete personal identity, each entity in that value chain only knows your identity as a consumer through its own separate lens. Their views differ from brand to brand. There’s no data crossover unless a consumer has OK’d sharing of information that each brand already has separately.

More consumer control, more trustworthy relationships

Your hardware store, your bank, and yes, Amazon – each of those brands have built up enough trust to get consumers to agree to hand over access to some identifiable data.

Maybe your bank isn’t only trying to sell you financial products. To generate a more trusting relationship with its customers, it might be providing helpful content. Pacific Northwest Credit Union Advantis is doing just that. In addition to allowing customers to skip a loan payment, the small financial co-op has relevant and welcome content on its website including an article featuring “5 tips for financial stability during uncertain times.”

These are examples of positive, relevant brand experiences – identity backbone builders. Not only is developing trust necessary to connecting with consumers in a cookieless world, it helps marketers build even more trust with them by enabling even better engagement.  Through partnerships with the right publishers, walled garden platforms, and identity resolution partners, marketers can connect with consumers to create trusting bonds and great brand experiences.

ABOUT THE WRITER

Devon DeBlasio is the Product Marketing Director of Identity and Privacy at Neustar. He is also co-founder and board member of the THREEE Marketing Council, a collection of advertiser, agency, and technology leaders working together to promote efficient, effective, and ethical marketing. Prior to Neustar, Devon lead Product Marketing at the shopping commerce platform, Curalate, as well as Sizmek (formerly PointRoll). 

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Everyone wants that elusive 360° view of their prospects and customers — but it’s harder to achieve than you think

How can you accurately assess your company’s data needs to find the right CDP partner?

The post Everyone wants that elusive 360° view of their prospects and customers — but it’s harder to achieve than you think appeared first on Marketing Land.

Nearly 60% of marketers surveyed say the biggest obstacle to their marketing success is creating a single customer view. Sound data unification and data quality processes are critical for a successful CDP initiative.

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The post Everyone wants that elusive 360° view of their prospects and customers — but it’s harder to achieve than you think appeared first on Marketing Land.