MarTech and AdTech Application Dominance in the next 12 – 18 Months

MarTech and AdTech Application Dominance in the next 12 – 18 Months

Think Big. Start Small. Fail Fast.

There has been plenty of hype you hear today in the media about Artificial Intelligence (AI), Machine Learning (ML), and Blockchain topics and their benefits. However, the reality is that the execution and adoption of those technologies are way behind in the enterprises. It is either because the use cases are not yet fully and immediately supportive to the business case other than it being fancy or that there is not enough skill sets within the organizations. Perhaps, the MarTech applications with those capabilities are still emerging every day and that marketers are confused what to do with them. AI and ML has been at the forefront when it comes to theoretical applications and very few organizations have productionized it to be useful on a day-to-day basis.
In this article, I will try to depict what the immediate future for MarTech and AdTech will look like in the short term, what I define as short term is 2018 – 2019 timeframe.
Here are the top five MarTech/AdTech applications that will be most talked about and implemented in the near-term.

Artificial Intelligence and Machine Learning:
AI and ML in marketing is headed towards where data is and how data is going to be leveraged in marketing. Most organizations are still spending time researching and preparing data. Hence the execution is gradually picking up. We will see a lot of small projects in the areas of AI and ML across various verticals especially in the B2C sector. Many MarTech applications will have embedded AI functionalities, for instance, campaign management applications having predictive email subject lines, web analytics applications having predictive personalization, content management systems having predictive cropping of images for responsive websites. Also, in the Machine Learning area we see more and more self-learning offers that are presented to the customers across all channels based on their past interaction with the brand. Although there is much talk about larger AI and ML applications, we will see some maturity with the MarTech applications with those offerings and we will see a lot small projects being implemented in marketing.

Everything Programmatic:
We have seen programmatic ads already quite popular across media companies. What we are going to see more and more is about programmatic Direct Mail where rendering an online experience into a direct mail piece and as people spend more time online on mobile, Programmatic Mobile advertising is becoming even more pervasive. Brands will want to use AdTech with capabilities not only on the programmatic display but also spanning across Direct Mail and Mobile with embedded AI and ML determining what channels are best for what individuals. This will leave marketers with no stone unturned in their efforts in programmatic advertising. What this means is that the audience the marketers used to target on specific channels will move to cross-device marketing to a single audience, i.e. making sure the same individual is seeing the ad across all the devices. Mastering cross-device targeting and optimized mobile ads will become more prominent across all the marketing efforts. People-based marketing will expand in the coming year as more players are able to support these efforts as identity resolution and ID graphs technology mature.

Server-Side Bidding: 
Although this has been much talked about in the last couple of years, it has not taken main stage yet despite server-side bidding promises to improve latency, solve for scale and support better auction logic to increase the yield.

In traditional header bidding most of the communications happen from the browser side into Exchanges. Essentially, these communications are moved to servers by eliminating the constraints on the browser side especially around user experience. This process is basically same as how SSPs and DSPs integrated for years, except this time the SSPs are integrating with each other as well which means SSPs will have to provide that infrastructure to support. Google and Amazon are already employing such techniques.

Server-side bidding is moving to videos as well now and this process helps provide a better yield for the publishers in determining the exact value of their inventory. Overall there are benefits using server-side bidding for publishers and exchanges and we are going to witness some big publishers and e-commerce brands moving towards this direction where the page-load time impacts the checkout rate. In the short-term we will see more transparent server-to-server superior connections that drive benefits for certain key brands contingent upon SSPs buy-in. If this takes off, then we are going to see some of the consolidations happening at the DSPs.

This is yet another topic that is talked about quite a bit and has been addressed via attribution modeling and this is one of the still biggest issues with marketers to really determine how their campaigns are performing. The attribution problem is exacerbated with the proliferation of channels and the fact that the data still resides in silos in those channels. As I see in the near-term, MarTech vendors that offer cross-channel customer orchestration applications are going to embed attribution modeling within the applications and it will no longer be an external analysis. Centralization of data pre- and post-activation (engaging customers and prospects with email, SMS, push etc.) becomes the norm whether it is within those cross-channel applications or within the centralized data environment so that these analyses can be done. Attribution will be much talked about especially amongst the lifestyle brands that are growing quickly, and they are not able to figure out why?

Finally, much hyped topic of Blockchain. It is all about trust. This is going to revolutionize how information is stored and exchanged across multiple entities with immense trust. Some pundits are even calling this “trust economy” that is going to ensue. There are several applications of Blockchain you would read across various media publications. However, when it comes to marketing; only thing that is talked about is Blockchain helping advertising technology. I also feel that MarTech will be embracing Blockchain when it comes to data, privacy and ownership. With the GDPR regulation already in full swing, will Blockchain provide that answer to store the data and provide that privacy that individuals need? Will there be more private blockchains that emerge among third-party data aggregators? We are certainly going to see small scale POCs in enterprise marketing using Blockchain concepts in 2018 – 2019 to validate if in fact Blockchain applications in data use cases will hold water.

In summary, organizations should Think Big, Start Small POCs to validate the concepts and scale, and fail fast if we have to so we can learn from the failures to make it better.

    Sukumar Muthya | VP, Marketing Technology

    Sukumar Muthya
    VP, Marketing Technology Ansira
    Sukumar has 24 years of customer-facing experience delivering technology solutions across industries, with 14 of those years delivering both marketing technology and analytics solutions. His expertise in customer engagement allows him to work with clients to understand their needs and translate those needs into finding the technology that delivers excellent results.
    Utilizing the best resources, Sukumar has delivered cross-channel digital marketing solutions (combining both AdTech and MarTech) to various clients in the Retail/CPG, Financial Services, Hospitality and Entertainment, Technology, and Auto and Manufacturing verticals. At Ansira, Sukumar successfully transitions solution sales to delivery through ongoing support and managed end-to-end activities, and serves as a single point of contact for customers.
    Sukumar has a Master of Science in industrial and systems engineering from Wichita State University, with Alpha Pi Mu excellence, and an MBA in international business from Thunderbird School of Global Management, with Beta Gamma Sigma honors.

    Why GDPR is a Blessing in Disguise for Event Marketers

    Why GDPR is a Blessing in Disguise for Event Marketers

    If you’re a marketer, you’ve probably had the date May 25, 2018 ingrained in your mind (likely in huge, flashing letters) for most of this year.

    If not, let me catch you up: this is when the EU’s General Data Protection Regulation (GDPR) went into effectcreating significant rules for how companies communicate with EU residents. GDPR is rooted in data privacy, with regulations that control how we collect, use, and store users’ data, as well as requirements to make data easier to access and delete.

    Even though May 25th has come and gone, GDPR will continue to impact event organizers with every event invite we send or piece of personal information we collect at registration.

    Here’s the good news about GDPR for event marketers: all of those long days and nights ensuring your events are compliant will pay off. In the long run, GDPR is actually a positive thing for your event marketing (which is good, because these regulations aren’t going anywhere).

    Here’s why GDPR is a blessing in disguise for event marketers:

    1. It keeps your event data safe
    When we host events, we capture a lot of personal data from our guestseverything from email addresses, to job titles, to dietary habitsand it’s imperative to keep all of that information private and safe.
    Good thing for GDPR, we’re now held accountable for the safety and privacy of our customer’s data. Not only will you need to closely follow your organization’s data security policies, you’ll also need to ensure you are sharing personal data securely and with consent (with sponsors, partners, and vendors).

    2. It forces you to clean up your data habits
    With GDPR, comes the dreaded data audit. This brings good news: now, you can stop putting off those best data practices you’ve always wanted to implement.
    You’ll now need to make sure your event data is up-to-date, your systems of records are synced and integrated with your event tech, and you’ve designated a single person in your organization to oversee all of these practices moving forward. This will ensure your data is accessible from one single place, and will enable you to avoid any database issues in the future.

    3. You’ll build more trust with your customers
    GDPR gives users more control over their data and it gives you the opportunity to build more trust with your customers and prospects. Complying with GDPR shows that you’re taking their privacy seriously, and being transparent about what you’re doing only adds to their trust in you.

    4. Your audience will be more engaged
    Yes, some people may opt-out and unsubscribe when given the opportunity. But you’ll know that the people who do remainin your database are there because they want to be in fact, because they chose to be. This means the people who receive your event invites or email promotions are more likely to actually engage with your communications, since they expressed that they wanted to receive this information in the first place.
    And what does a more engaged audience really mean? More clicks. Faster responses. More RSVPs. More meaningful attendees. Increased conversions. Even though your database might be smaller, your post-GDPR event marketing efforts will be much more impactful. And I’d take that type of quality over sheer quantity any day.

      Farmer Boy

      Ben Hindman
      co-founder and CEO of Splash
      Ben Hindman is co-founder and CEO of Splash, the fastest-growing end-to-end event marketing technology used by over half of the Fortune 500. An event planner turned tech entrepreneur, events are in Ben’s DNA. Prior to starting Splash, Ben was the Director of Events at Thrillist, where he produced large-scale events from concerts to mystery fly-aways. He is also a co-founder of the Summit Series, the renowned invite-only destination event for the greatest minds in tech.

      Segmentation and Persona Building With MarTech

      Segmentation and Persona Building With MarTech

      MarTech has traditionally focused on the execution of marketing and advertising campaigns. Whether it is DSPs, DMPs, content marketing, acquisition, etc., MarTech stacks concentrate on the implementation of marketing campaigns. However, as MarTech data becomes more diverse, there is an opportunity to help on the front-end of marketing campaigns—through segmentation and persona building—enabling marketing strategists to create more holistic pictures of their target consumers and ultimately increase marketing ROI on the backend.

      What is segmentation and persona building?

      Customer Segmentation is the practice of grouping sets of similar people (customers or potential customers) based on distinct needs or characteristics. Segments are typically developed through large-scale market research and defined using demographic information like age, ethnicity, or location. Segments can also be created using psychographic and behavioral information like interests, opinions, values, lifestyle, or lifestage. Customer segments don’t provide insights into a specific consumer, but rather groups of consumers within a broader marketplace. These groups can help marketers differentiate between the different types of customers that exist and the interests of those customer groups.

      Personas are fabricated characters created by marketers to approximate real customers. They are generated based on profiles, which include demographic information collected through research of real people. These profiles are meant to be a direct representation of a customer cohort that shares similar values, behaviors, and aspirations. Personas begin with basic profiles, but then are given names, faces, personalities, and families, to paint amore vibrantpicture of what that person would want and need in real life. Personasadd the emotional and behavioral component to marketing—the more human element. Once complete, personas can help determine need state or end goal for a particular consumer, so that your brand knows how to target them precisely and what messages or calls to action will resonate with them. 

      How MarTech Enables Segmentation and Persona Building

      Both customer segmentation and persona building rely on a wide variety of data sets ranging from first-party survey data, qualitative focus groups, purchase data, behavioral data, and online tracking data. Segmentation and personas have historically been built from one or maybe two data sets. With the advent of MarTech and big data processing technologies, segmentation and persona building has entered a new era. With the ability to combine a massive amount of data from different sources, MarTech enables segmentation models and personas to extend beyond simplistic views of consumers to robust frameworks that combine the best of segmentation and persona building in an instant.

      This powerful segmentation and persona hybrid has infinite potential for marketing and brand strategists willing to jump into the MarTech world for their research needs. Gone are the days of having to wade through multiple syndicated reports, client data, and click data to build segments and personas. MarTech tools such as ThinkNow ConneKt combine first-party, behavioral, and custom data to enable strategists to createsegments and personas that allow marketers to hyper-target users in a fragmented media environment.

        Farmer Boy

        Mario X. Carrasco
        Co-Founder & Principal, ThinkNow
        Mario X. Carrasco is Co-Founder and Principal of ThinkNow, an award-winning, technology driven cultural insights agency based in Burbank, Calif. Mario’s expert knowledge on multicultural consumers is evident in his contributions to Hispanic Millennial Project and We Are GenZ studies. Mario is a contributor to Forbes, eMarketer, Quirk’s Magazine, Online MR Magazine, and MediaPost. He presents at industry conferences such as the Google Multicultural Marketing Forum, Vision Critical, and Hispanicize LA. He is the SBA 2017 Young Entrepreneur of the Year Award recipient, an SBA Emerging Leader Recipient, Stanford Latino Entrepreneur Institute Graduate, and USC Marshall School of Business Graduate.

        How to take a more agile approach to consumer understanding

        How to take a more agile approach to consumer understanding

        By Mark Walker, Revenue Director, Attest

        Does anybody reading this remember when most new products and technology were developed with the ‘waterfall’ approach?

        For those who don’t, here’s a quick primer.

        In a nutshell, the waterfall approach to launching new products was to try and gather as much information on the end-product as possible, define all its requirements, then go through every phase of the development cycle, before finally launching a fully functional new product to the market.

        The problem? Very often, the final product wasn’t what the market needed (or wanted), and by waiting until the very end to find this out, incredible amounts of time and money were wasted.

        From waterfall to agile

        The solution? Agile software development, characterised by shorter development cycles (sprints), allowing for rapid feedback and iterations, which reduces risk and leads to better outcomes by discovering bugs or feature deficiencies earlier.

        Thankfully the agile approach to product development has been very widely (if not universally) accepted and adopted, and the result has been an explosion in productivity, speed to market and successful launches.

        Yet away from software development, the waterfall approach is still the de facto way of working. Take for example the approach to market research, consumer insights and brand development.

        Playing catch-up

        When a business needs to refresh its brand, learn more about their market or develop a major creative marketing campaign, they will often start with market research.

        While the idea of gathering insights from consumers is fundamentally a good one, the approach is anything but.

        Typically an agency is called in. Briefs are written. Sub-contractors handle scripting, fieldwork and the like. Hundreds of emails, dozens of conversations and several weeks later a giant PDF report is presented and then circulated round.

        You have to make major decisions based on this output, though you realise – once it’s too late – that you should have asked something slightly differently, or another question entirely that wasn’t obvious at the time. But you’ve sunk too much time and money into the project at this point, so you make do.

        Just like less than stellar product or technology outcomes delivered by waterfall methodologies, traditional market research is slow and cumbersome, leading to poor levels of consumer understanding for organisations, all while costing more!

        Sadly this approach is still prevalent across most established businesses.


        Introducing scalable intelligence

        But a better way is emerging, based on speed to insight, agile feedback, organisational collaboration and rapid iteration that matches the modern velocity of decision making.

        This approach is known as scalable intelligence, designed to meet the needs of modern organisations, and a world where things change ever-more rapidly.

        In just the last couple of years we’ve suddenly seen the emergence or voice-enabled shopping and search, autonomous cars and drone deliveries. Social commerce, artificial intelligence and the internet of things are rapidly developing fields.

        Combine these seismic technological changes with the economic, social, political and cultural shifts that impact consumers almost daily and any business that relies on sporadic, project based market research can be sure to be left behind.

        So, how can your company adopt scalable intelligence? Much like the shift from waterfall to agile in product and technology, there are three key elements:

        1. Culture

        Most importantly, organisations have to adopt a new culture and philosophy towards consumer insight. If there isn’t a commitment to the adoption of scalable intelligence, then clearly it won’t take root.

        How do you know if you’re ready to embrace a new way of gathering consumer insight? Ask yourself (and your colleagues) these questions:

        • Do we value an open, direct dialogue with consumers?
        • Are we seeking to align the volume of insights with our rate of decision making?
        • Will speed and agility give us an edge on our competitors?
        • Are we seeking to be more collaborative and share insights across functions?
        • Can an iterative approach to insights reduce decision-making risk and lead to better outcomes?
        • Is it ok to admit ‘we don’t know what we don’t know’ and be open to unstructured learning?

        Ultimately if your company culture embraces (or seeks to embrace) speed, agile decision making and iterative learning then you should be in a good place to adopt scalable intelligence.

        1. Workflow

        If market research is defined by writing comprehensive briefs and running RFP processes, then scalable intelligence is defined by outcome-led sprints.

        Much like waterfall application development necessitated huge teams and complicated sign-off processes, traditional research requires huge amounts of planning and internal sign-off due to the cost and complexity of running major catch-all projects.

        With scalable intelligence, much smaller autonomous teams can work dynamically to answer important business questions as they arrive. The workflow involves:

        • Identify a gap in your consumer knowledge or a major event that you need to better understand
        • Define the business outcome and desired actions you’d like to take
        • Run a small open-ended survey to learn and gather initial feedback from
        • Refine your questions and approach based on these initial learnings
        • Share across the team for feedback and to uncover any missed opportunities for deeper insights
        • Repeat as necessary to built up a layered, rich and statistically robust answer to the original question.

        This approach keeps things nimble, while also spreading knowledge across teams so the whole organisation benefits.

        1. Tools

        Initially the agile approach to product development was one that spread based on culture and new workflows; but eventually it led to the need for new technologies that mirrored and enabled the agile methodology. Tools like Jira and Asana became huge players as they facilitated a better way to work.

        Similarly there has been a gradual shift in attitudes to gathering consumer insight, with more and more leaders recognising the need for a more agile and iterative approach that can scale across the whole organisation, keeping everyone closer to consumers.

        Against this backdrop, more specialist technology providers have sprung up to support organisations looking to adopt scalable intelligence in place of traditional market research.

        Attest is one of those leading providers of scalable intelligence, helping businesses to quickly get their whole organisation closer to consumers, match the volume of insights to their rate of decision making, and reduce the risk, cost and complexity of getting the right answers to their core business questions.

        In conclusion

        If you’re looking to adopt a more agile approach to consumer understanding, then you’ll need to ensure your organisation has the right culture to support it, a commitment to developing new workflows, and that you invest in specialist tools that will accelerate the benefits you’ll see from scalable intelligence.

          Farmer Boy

          Mark Walker
          Marketing Director, ATTEST
          Mark Walker is an experienced B2B commercial leader and award winning content marketer.He is currently the Revenue Director at Attest, a fast-growth scalable intelligence platform, helping connect brands and agencies to networks of 100 million consumers across 80 different countries.He writes and speaks regularly about all things digital, marketing and content; and he loves to learn and connect with others interested in the trends shaping our future.

          AdTech Meets MarTech: Using Email to Deliver Precise Personalization

          For many companies, customer acquisition and customer retention seem to exist in two separate vacuums. The advertising and lead gen functions happen on one side of the marketing house, while the customer relationship nurturing happens on the other.

          Bringing the two together has long been recognized as a tremendous opportunity, but also a problem, especially across channels. With ads targeted based on cookies and devices, there’s been no reliable way to link new incoming clicks and leads to existing CRM data, until the lead actually converts. And thus, marketers have missed a valuable opportunity to learn about potential customers’ interests and intentions until they’ve officially made a purchase.

          It’s even more complicated on social platforms and mobile apps. Lacking any authentic way to engage with potential leads, marketers’ only option is retargeting—continually hitting the same leads with ads until they (hopefully) convert. Only then can they begin monitoring and leveraging behavioral data to refine personalization with accurate relevancy.

          The Data Disconnect

          Historically, technology has been largely responsible for these silos. Digital AdTech, including programmatic, real-time bidding and direct buy has become an industry of its own, focused on bringing in new customers. Meanwhile, MarTech solutions like CRM and marketing automation platforms track customer data to a persona, allowing marketers to leverage known behavior and profile data to connect with customers already in the database.

          Bringing AdTech and MarTech together would enable marketers to form a one-to-one relationship with customers at the very top of the funnel across every domain and nurture that relationship meaningfully throughout the buyers’ journey. Because customers’ expectations around personalization are extremely high, this would not only create a richer, more relevant experience for customers but also a better revenue opportunity for marketers. A win-win, right?

          Tearing Down Silos

          Until now, there’s been no viable way to connect the dots. Marketers know that AdTech breaks the ice and MarTech continues the conversation, but that transition point has been missing. The ability to send AdTech leads into the MarTech funnel before the point of purchase has been elusive, lacking a “connection” between the two platforms. The addition of multiple channels—namely social and mobile—have added to the siloed problem.

          Now, a new approach is enabling MarTech to reach its goals at the scale of AdTech, delivering personalization for millions of audience members. And, you might be surprised to learn that it’s email powering the convergence.

          How Email Drives Convergence

          Once considered “old school,” email is experiencing a renaissance for its ability to serve as a unique unifying identifier, providing the missing link between lead data and CRM data. This capability, which enables the convergence of AdTech and MarTech is giving marketers a powerful new way to precisely personalize and target potential and existing customers based on known behavior.

          Here’s why email works for convergence:

          • It’s ubiquitous. Virtually every channel requires an email address for subscribers—including social and mobile apps. By connecting these channels, email allows marketers to tie behavioral data collected over time across multiple footprints to an individual. Technology can recognize the same individual on the web, on Instagram, on Facebook, etc. and tie these marketing experiences together into a cohesive personalization program.
          • It’s tied to an actual person. Unlike a random user name, an email address belongs to a real human. This not only helps reduce paid impressions wasted on bot social accounts, but also overcomes the issue of multiple accounts for the same user. Even an Instagrammer with multiple accounts will likely use the same email address to register them. Email personalization lets marketers target that user accurately on every account.
          • It’s more accurate than cookies and device targeting. The trouble with browser cookies and device targeting is that they’re often shared, and they can’t distinguish one user from another. It’s not unusual for multiple family members to use the same laptop or tablet, for example. But email addresses are very rarely shared. They’re unique to the individual, which makes targeting and personalization based on email much more accurate.

          Why worry about convergence anyway?

          Converging AdTech and MarTech makes for a better experience for both marketers and consumers. And, it’s necessary for keeping up with the demands of modern marketing. Modern audiences are technically savvy, demanding experiences that are more attention-grabbing and relevant. Therefore, publishers and other platforms are moving toward convergence, giving brand marketers enhanced capabilities for targeting and personalization.

          By leveraging email as the unifying identifier, marketers can achieve better data centralization, smooth the acquisition-to-relationship-building transition to eliminate the disconnect between AdTech/MarTech platforms. And, it helps to eliminate the silos between channels by connecting them all through one attribute.

          This singular identifier also provides a singular customer view, where marketers can track and better understand customer behavior, and thus provide a more cohesive, relevant experience across every channel.

          Marketers also benefit from meaningful scalability—as leads come in (through AdTech), they can be instantly connected/funneled into the MarTech process to begin tracking and personalizing content and targeting immediately. At the same time, personalization becomes much more accurate, driving higher engagement and better customer satisfaction. This also lowers the cost of re-acquisition for lost customers because they don’t appear as new leads, but instead as returning customers.

          With less friction in the process, measurement accuracy also improves. Companies can establish uniform KPIs and metrics to gauge success, which resonate with both marketing and sales to enable collaboration and a more cohesive effort, thus driving more revenue and overall business growth.

            ABOUT THE AUTHOR
            Farmer Boy
            Jeff Kupietzky
            Chief Executive Officer, PowerInbox


            Jeff serves as CEO of PowerInbox, an innovative technology company helping companies monetize their email newsletters through dynamic content.  Before joining PowerInbox, Jeff served as President and CEO at, managing worldwide operations and building Oversee’s owned and operated portfolio of domain names into one of the world’s largest, establishing the company as the leader in Internet real estate. Under his leadership, the company diversified into lead generation, building several high growth and high margin businesses. Before that, Kupietzky served in leadership positions with X1 Technologies, Digital Insight (Intuit), Siebel Systems (Oracle), and Loudcloud/Opsware (Hewlett-Packard). Jeff began his career as a consultant for McKinsey & Co., developing business strategies for software, insurance and banking clients. A frequent speaker at Digital Media conferences, he has also been featured on CNN, CNBC, and in many news and business magazines. Jeff earned an MBA with high distinction from Harvard Business School and graduated Summa Cum Laude with B.A. in Economics from Columbia University.

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