• Amazon sellers battle the giant’s algorithm-based policy- and decision-making

    Amazon sellers battle the giant’s algorithm-based policy- and decision-making

    “Their algorithms are garbage,” said Lesley Hensell Demand, partner in Riverbend Consulting, a firm that helps Amazon sellers overcome a host of challenges, including account de-activation and loss of ASINs (a kind of ISBN number Amazon assigns to products. Riverbend is heavily staffed by former Amazon employees.There was a lot of discussion about Amazon’s algorithms at the AMZ Innovate event for Amazon sellers in New York City this week. The reason: Amazon sellers are deeply invested in a platform which is essentially too big to be held accountable. They’re at the mercy of policy-making and enforcement which can seem capricious or even be downright mystifying.Hensell Demand offered a grim tour around the problems sellers can face. Amazon attempts to exert control over pricing decisions by third-party sellers. If, for example, it sees a product from a seller listed at a lower price on a competitor website, it will enforce a price reduction. Because the process is automated (those algorithms), it’s not uncommon for Amazon to confuse a “pack of one,” say, with a “pack of three.” If Amazon believes it detects systematic over-pricing, more penalties can follow.And then there’s the reported practice of simply copying a successful product and putting Amazon branding on it. According to Hensell Demand it has even been known for Amazon to approach the manufacturer and offer to place a larger order than the successful seller.Sellers and aggregatorsThe event, put together by Jared Orkin, VP of Product Strategy at Adbeat and an Amazon and Shopify expert, and Brandon Furhmann, a successful Amazon Seller with his own Kitchenware Brand, did not just attract sellers. Also there were the partners who offer services for sellers: PickFu, the consumer research vendor, and GETIDA, an Amazon auditing service, for example.Also present were a number of aggregators like Thrasio and Boosted. These companies are in the business of acquiring and growing FBA (fulfilled by Amazon) sellers — developing symbiotic portfolios of businesses that allow cross-selling and cross-promoting. Keith Richman, co-founder of Boosted, painted almost as bleak a picture of the space as Hensell Demand, but not without a ray of sunshine.Online advertising is getting more expensive and difficult, he said. There’s no end in sight to the supply chain crisis. It’s really hard to hire talent right now. Amazon’s policy making and rule enforcement is hopelessy inconsistent. Sellers are under constant threat of being de-listed. And yes, success means the risk of being copied by Amazon, or indeed by other sellers. “Why is everything so hard?” he asked.Things might be hard at present, but Richman also painted a rosy picture of the future. Massive changes are underway, he said, in digital shopping habits, fueled in part by social media. Consumers are open to trying new brands as never before. Established companies often lack the agility to respond to these changes. “This is just the beginning,” he said.PPC, coupons and keywordsThis mixture of horror and hope set the backdrop for much more granular explorations of how sellers can simply push their products to the top of Amazon’s search results. Casey Gauss, VP of SEO at Thrasio (a college dropout and self-taught programmer) came armed with actionable advice.To get the prized Amazon Best Seller badge, for example, consider switching your product from its existing category to a sub-category where you can beat the competition. Purse a “big coupon” strategy, offering significant percentage or price discounts for a limited time, then gradually phasing them out (25% off for two weeks, then 15% off, and so on). Refresh your keywords regularly. Invest in PPC campaigns.Most importantly, said Gauss, do all these things together. You might only be making “micro-improvements,” but your listing in the search results will be headed in the right direction.Living with a giantThe event felt like a tribe of Davids all trying to make peace with the giant Goliath. Slaying the giant is not an option. They’re angry at many things the giant does, but they’re also fascinated by his quirks, needs and moodswings. We commented to Furhmann that the relationship between Amazon sellers and Amazon looked not unlike the relationship between search marketers and Google. He agreed.“All these big tech companies are the same,” he said. Rather than devoting adequate human resources to executing policy, “they trust the algorithms — and the algorithms make really bad decisions.” It’s not just Amazon, he said. The same complaint could be levied against Facebook and Google.“That’s where the frustration springs from.”New on MarTech About The Author Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space. He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020. Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.

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  • 3 tips for winning with real-time, inventory-driven ads

    3 tips for winning with real-time, inventory-driven ads

    Q4 is here, and it’s time to ensure your paid search programs drive the success you need for a strong finish in 2021.  Two short years ago, typical steep discounts and strong promotions were big factors in driving Q4 e-commerce success. Then COVID hit and upended the world. Then 2021 hit with massive strains in supply chains and escalating shipping costs. These factors mean marketers cannot assume vast inventories or even alternative products to satisfy their customers.  Take, for example, the auto industry. Dealerships cannot get adequate inventories of new vehicles. They are pre-selling allotted vehicles before they even hit the lot, and they wish they had more cars to satisfy huge demand, including for used vehicles. It’s more crucial than ever to reduce ad waste and connect a buyer’s search with THE specific car they are searching for online. Similar challenges confront countless other industries in 2021.  To win during Q4, your PPC campaigns need to be far more responsive to real-time inventory and other stressors that are flummoxing many marketers. Here are three tips for executing on the new game plan that can help you win as supply chains wreak havoc on your competitors’ campaigns. The three steps outlined below won’t solve every problem in Q4, but these steps can help you conquer some of the most pressing challenges marketers are facing in the coming few months:  Step 1: Connect your ads to real-time supply chain and inventory data After all, you can only sell what you’ll ACTUALLY have on hand or on the way. By connecting real-time data right into a PPC workflow, marketers can pivot quickly and automatically when one line of product sells out, and a much-delayed shipment finally arrives.  Automated ad creation instantly reflects the new inventory and makes it possible to serve up ads for only the items you can actually deliver. And when automating ads from inventory, there’s no need to stop at simple text ads. Extend the automation to also create RSAs (Responsive Search Ads), RDAs (Responsive Display Ads with images), and DSAs (Dynamic Search Ads).  Next, use the automation to add hyper-relevant targeting criteria like keywords to serve ads against product-specific searches, including for users who are searching for attributes that align with your inventory data (in the instance of vehicles, think about make, model, color, year, mileage, etc. – or size, color, and other attributes relating to apparel or other products).  This alignment of inventory data and your PPC programs also allows for automated creation of ETAs and DSAs along with the most popular ad extensions. With RSAs becoming the default ad format, this is a great time to add RSA to your whole account and align your inventory data with ad creation.  Another nice outcome – when inventory is gone, ads for that product stop, which helps eliminate wasted spend (and frustration for customers). This simple first step gets you on the right track, and you should see benefits quickly.  Step 2: Optimize your feed to show better ads While structured data like that found in spreadsheets is commonly used by PPC teams, automatically turning that data into ads may present some problems, especially when the data feed wasn’t built specifically with PPC ads in mind. The problem is that data may be formatted inconsistently, incorrectly, or certain required fields to run ads are simply missing. This is when the need arises to optimize the feed data, a process that must be automated with rules if the advertiser hopes to gain the full time-saving benefits of data-driven ads.  The data advertisers have access to usually originates from a shopping cart system and may not follow all the strict requirements for what Google needs for ads. For example, the product titles may be too long to fit in an RSA headline component or to fit the title element of a shopping ad. Or the product category data may not map cleanly to Google’s product categories. This is when you will need to optimize the feed before using it to advertise. Optmyzr’s Feed Optimization is used to fix an inventory data feed so it plays more nicely with Google Ads The Feed Optimization tool simplifies things like: Creating product titles that follow Google’s best practice guidelines. Many data sources are not inherently Google-friendly. Feed Optimization is designed around those guidelines. Standardizing attributes such as colors and sizes. For example, simply replacing all instances of “M” with “Medium” or replacing unusual color names such as “cardinal” with more common references such as “red” result in more impression volume because your keywords are better matched to how users search.  Think of the impact on automatic creation of relevant ads when the source data is aligned properly. Cleaner inputs = more powerful outputs.  Step 3: Use Google’s Drafts and Experiments to explore what works best.  With new data-driven ad strategies in place, it’s time to start testing what works best and prove to your stakeholders that the new strategy is paying off. Drafts and Experiments is a feature-rich tool from Google that offers a lot of horsepower for search marketers but isn’t the most intuitive, fluid add-on in the Google environment. For example, monitoring experiments in Google across more than one account or across multiple experiments can be cumbersome.  Free scripts or PPC tools like those from Optmyzr can help you see all experiments across accounts in more user-friendly ways, with results and recommendations served up on a single page. The streamlined views via Optmyzr make it much easier to monitor the experiments and take actions according to the results.  Optmyzr’s Campaign Experiments Dashboard brings together all the experiment results from across an entire MCC account to make it easier for PPC pros to test and iterate more quickly.  The best PPC practitioners are really good at experimenting. They test, learn, and iterate – and the faster they can do all of that, the more they leave competitors in the dust.  Masters of automation & optimization become masters of PPC Paid search pros benefit when they are in the greatest control of the automations at their disposal. The steps noted above can really help position PPC pros to tackle the ever-evolving challenges that confront marketers in Q4 of 2021. The challenges are big, but so are the opportunities to drive exceptional results. Approach Q4 methodically and think automation and optimization at every turn: Connect real-time supply chain and inventory data with PPC adsSupercharge your data with feed optimization tools that sanitize and standardize the info your PPC management system needs for higher-performing adsExperiment, test, react and optimize faster if you want to grow faster Remember – focus on using automations to remove those task-heavy activities of PPC from your plate. Those who master the automations and then use powerful tools that further free up time and energy for more strategic endeavors are the ones who will have the advantage in the daily battle for paid search dominance.  We’d love to talk to you 1:1 and give you a demo of how Optmyzr and Campaign Automator go beyond platform-level automations. Empowered PPC pros are the ones who will win! Talk to us about how to get that empowerment right on your desktop. We even offer free trials so you can get started without risk. Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here. About The Author Optmyzr’s PPC management platform provides intelligent optimization suggestions that help advertisers across the world manage their online advertising more effectively. Optmyzr connects with Google Ads, Microsoft Ads, Amazon Ads, Facebook Ads, Google Analytics, Google Merchant Center, Google Sheets, and SA360. The company was founded by former Google AdWords executives. The Optmyzr PPC suite includes over 30 tools to improve Quality Score, manage manual and automated bids, find new keywords, A/B test ads, build new campaigns, manage placements, automate budgets, and automate reports. Optmyzr was named best PPC management software at the 2020 US, UK, and Global Search Awards.

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  • The Real Story on MarTech: Navigating the new world of consumer privacy

    The Real Story on MarTech: Navigating the new world of consumer privacy

    Marketers and advertisers are facing choppy waters at the confluence of two powerful currents: a vigorous new era of consumer data privacy, rolling into “data-driven everything” practices like personalization and programmatic advertising — both now turbo-charged by artificial intelligence and machine learning. The increasing pace of privacy legislation, privacy-protecting tools and advocacy, and the market-shaking actions by Apple and Google to limit cross-device and cross-site tracking have left all parties scrambling for secure footing. Vendors vie for position with new and updated solutions and alliances in a race for adoption — even as the course continues to shift. Here’s the timeline on Google’s 3rd-party cookie phase-out. With everything in flux, as a marketing leader you might be tempted to crawl under your desk and wait for the dust to settle. Where to begin? Indeed, how to begin when everything is so fluid? Start with a framework When faced with a chaotic and unsettled situation, a good place to start is with an organizing framework to categorize and understand the issues, dynamics, challenges, and opportunities in such a way that you can take action. Given all those cross-cutting currents, at Real Story Group we decided to apply a change-and-adaptation model. We’re calling the resulting reference framework “New World for Consumer Data.” A complete report is available to RSG subscribers, but I’ll summarize the findings here. From left to right: key factors fueling change, what’s under threat, the resulting challenges, and emerging responses. Source: RSG Privacy change drivers Color-coded in gold, these five factors are catalyzing big shifts in the data landscape. Third-party cookie deprecation If you think of the advertising and marketing ecosystem as a Jenga tower, Google’s announcement that it intends to withdraw support for third-party cookies in its market-dominating Chrome browser is the move that set the entire structure atremble. Programmatic digital advertising has long relied on third-party cookies to enable real-time bidding, auctioning the attention of web page visitors to advertisers looking for particular audiences. Mobile information sharing limits Apple got the ball rolling by giving its mobile device users more control over data they share with the applications they use. Google’s Android is following Apple’s lead, albeit at a slower pace and less aggressively. Regulatory acceleration Europe’s General Data Protection Regulation (GDPR) broke the ice, taking effect in 2018. Similar regulations have been and are rolling out around the world, most recently in China. Here in the U.S., we face a state-by-state patchwork of regulations, with California’s CCPA taking effect this year — to be followed in 2023 by CPRA, Virginia’s CDPA, and Colorado’s Privacy Act. Consumer awareness Surveys reveal a public that is increasingly sensitive to the visibility of their online activity and the vulnerability of their data. Defensive services like ad blockers, privacy browsers, privacy search engines, and burner emails are proliferating to meet the demand. Security vulnerability Data breaches are increasing in frequency and scale at enormous cost to both organizations and the individuals affected. Specific challenges The report maps each Privacy Change Driver to a subset of the seven Specific Challenges (denoted in red in the diagram above). For example, by limiting access to perishable, proximate identifiers used to match ads and marketing to users—and to measure the effectiveness of such efforts— three Specific Challenges arise: Reduced Efficiency: Eroded ROAS – The ability to buy media centrally, programmatically, and with surgical user-level targeting has been credited with more efficient ad spending.Reduced Revenue: Acquisitions Decline – Reduced ability to fine-tune ad placement and messaging.Fewer Analytic Insights – Data-driven analysis informs an array of business decisions; loss of such data may well ripple through the entire enterprise. Emerging responses RSG’s report digs into twelve emerging responses, evaluating each three ways: Marketer Pros and ConsReadiness for adoption by advertisers and marketers on a scale from low to highScoring for how well it addresses each specific challenge on a scale of 0 to 4 Here’s a short summary of those twelve, and what role each potentially plays. Walled gardens Already dominating digital ad spend in the U.S., Google, Facebook, and Amazon may grow their share as advertisers and marketers addressable audiences at scale. Private gardens Retailers and media with monetizable first-party data are building out their own closed advertising ecosystems. Universal shareable IDs Multiple candidates (80+) vie to replace the third-party cookie and grease the wheels of programmatic advertising. It’s a crowded field, very much in flux, and the utility of any one ID will largely hinge on broad adoption. Differential privacy/cohort targeting This refers to the fluid and experimental methods being explored to somehow enable both ad-supported media and consumer privacy. Google’s Privacy Sandbox includes a number of proposals, most notably FLoC, which is still evolving under plenty of scrutiny. Contextual targeting This legacy method may experience a renaissance not only because of third-party data deprecation but because new technologies like artificial intelligence and machine learning promise a more effective, more automated iteration of the approach. Data exchanges and partnerships Cleanroom technologies and services promise to enable the chaste sharing of pseudonymized data (or data attributes and models) among business partners and within exchanges. The technologies may be simpler to untangle here than the questions around consent. Cookieless ID graphs There are plenty of other signals aside from 3p cookies that, when combined with machine learning models trained on determined identities, can suss out probabilistic identities. Remember the meme, “on the internet, nobody knows you’re a dog”? Now they do. First-party data emphasis When DTC (direct-to-consumer) first popped up as a phenomenon, eating into the revenues of more traditional through-channel incumbents, the value of a direct customer relationship and attendant first-party data came into sharp relief. Add on the deprecation of third-party data and businesses of all types are either undertaking or considering a purposeful effort to directly collect data (and consent to use it) from their customers. Using that information to reach and acquire net new customers is another matter. In-session targeting Adjust visitor experiences on your web properties based on real-time, in-session user behavior. Active stewardship Take a leading position with proactive policies and practices to safeguard your customers’ data. First movers may win a competitive advantage. Privacy/compliance management A growing pool of privacy tech vendors promise services and automation to help manage the increasingly complex array of regulations. Consent management Whether sold as part of a broader compliance suite or as a stand-alone, the execution of such tools is key. Heavy-handed or too-clever approaches may not only confuse consumers but also cause brand damage. That’s a lot of choices … Does that seem like a lot of responses to you? Well it is, and you should recall your myriad options when vendors coming calling with a single magic bullet — – because there aren’t any. The key then is to focus on fit for your particular circumstances. Each enterprise will need to ground its decisions in a solid understanding of its own brand, risk tolerance, philosophy, and so on. Read next: Google’s FLoC poses a threat to identity resolution and advertisers. Take for example “First-Party Data Emphasis,” a seemingly uncontroversial response. Yet there is much to consider, such as the associated data management effort and risk that increases proportionately with a growing trove of customer data. You’ll need to address questions around whether to share that data, for what purpose, with whom and how. Not to mention consent and compliance. For some organizations, a focus on data minimization might be a preferred approach. Or maybe first-party data emphasis is governed by specific standards and guided by a philosophy of collect-only-what-adds-customer-value data minimization. What you should do RSG’s report offers several recommendations, and I’ll share two here. First, benchmark. Do the analysis to estimate, for example, the effect Google’s cutting third-party cookie support on Chrome will have on your media spend and its contribution to sales. A good understanding of the potential impact will help inform your planning to meet the challenge — and help feed any associated business case. Second, consider pulling together a cross-functional team, ideally with executive sponsorship. This is a complex and high-stakes set of issues that invite a shared organizational approach that includes voices from legal, privacy/compliance, security, data, and tech — as well as marketing. Regardless of how your company ultimately decides to proceed, a holistic approach means more perspective, more information, and broader awareness. What comes next This is a fast-moving environment, so I’ve found it pays to monitor signals from larger enterprises and the marketplace as a whole. Look for more in these pages as we share what we learn. Real Story on MarTech is presented through a partnership between MarTech and Real Story Group, a vendor-agnostic research and advisory organization that helps organizations make purchasing decisions on marketing technology applications and digital workplace tools. New on MarTech

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