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balance and avoid emails with large images and little text that can trigger spam filters use a clear hierarchy through proper html heading tags bullet points and short paragraphs create meaningful copy to improve engagement which can affect sender reputation top tip it s worth knowing about the changes google and yahoo made for bulk senders of emails 5 000 per day in 2024 these new standards impact three key areas unsubscribe and opt out links spam threshold and email authentication what are the best email accessibility testing tools you may have been diligent and followed all the guidelines and best practices for an email campaign but there could be something you missed that s where testing comes in before you launch any workflow or campaign use accessibility testing tools to spot issues that are easy to overlook such as color contrast or missing alt text or tags let s look at some of the best email accessibility testing tools to ensure your communications are accessible to everyone on your list litmus an all in one tool that can evaluate accessibility for users with visual impairments and those relying on assistive technologies it includes visual impairment filters checks for over 40 accessibility criteria offers nvda screen reader previews and supports text justification and language attribute checks nvda this free screen reader is available for download for windows that reads aloud page content and relevant semantic info such as headings lists and links accessible email you can detect missing links alt texts and other accessibility issues and check email code for compliance with screen readers stark a plugin for figma sketch figjam and adobe xd this tool can check contrast ratios scan design files in the development stage and provide real time reports to address accessibility issues proactively color oracle a free desktop app that applies real time color blindness filters to your screen and helps you visualize how your design will look to users accessible colors this tool allows you to check the contrast of text and design elements webaim s color contrast checker this evaluates contrast ratios between text and background colors stripo email accessibility checker this free tool helps check whether your images have alt text and can generate any missing text with artificial intelligence ai in the editor voiceover a screen reader built into mac devices that reads aloud page content and relevant semantic info such as headings lists and links axe devtools an automated accessibility testing tool that helps you find and fix accessibility issues early in web development in a browser photosensitive epilepsy analysis tool peat this tool checks that your gifs comply with the recommended limits on flashing frequency how to use ai to improve email accessibility the widespread adoption of email automation as well as ai tools and platforms is helping enhance marketing through personalization predictive analytics and efficiency improvements email is no different as ai is being used to personalize and tailor content optimize send times and segment audiences but the technology can also be used to improve email accessibility use ai tools for copywriting ai can support almost every stage of your writing process from research to optimization the key is knowing when to use it and when to step back in with human judgment discover some of the most practical ways to use ai in your email copywriting by reading our blog using ai tools for copywriting improve readability simplify language make emails easier to understand for users with cognitive disabilities by using ai powered readability tools a tool such as readable can assess the readability of your email content you can also use tools like chatgpt claude or grammarly to check text for errors tone or readability and can provide rewrites for example anishta shedha communications manager at amazon suggests a prompt of simplify the language in this email to make it accessible to a broader audience top tip google is integrating gemini ai into gmail to generate summaries of email threads by highlighting key points so if an email is image heavy with very little html text the system may struggle to interpret and summarize the text as the only readable content is fragments of html text such as navigation links or footer copy auto generate alt text screen readers rely on alt text to describe images and an important part of accessibility ai can help create alt tags automatically by analyzing image files and generating descriptive screen reader friendly text use the power of ai through integrated email builders such as klaviyo mailchimp activecampaign to analyze images and create descriptive and relevant alt text ensure proper structure ai driven quality assurance tools like litmus can evaluate an email s html code to ensure the headings h1 h2 h3 and proper list structures are intact this ensures screen readers can navigate your content easily run automated qa checks an ai assisted design solution like smart check can scan text links and color choices these types of tools highlight elements that hinder screen readers making them faster and easier to fix litmus email testing and wave can help with this use high contrast colors as we ve mentioned high contrast ensures readability for all users including those with visual impairments use a tool like colour contrast analyser to check and adjust contrast in your emails create descriptive links descriptive links help users understand where a link will take them especially when using screen readers use accessibility checker tools in email platforms to review link descriptions to ensure they are accessible questions to ask before sending an email before launching any campaign you should ask yourself can the email be understood without images are cta buttons descriptive and easy to tap is the text readable on mobile devices does the email work in dark mode is the color contrast sufficient does the email work with screen readers have alt text and semantic headings been added is the content easy to scan and understand has the email been tested across devices and inboxes can every subscriber engage with this content easily conclusion there s a lot to consider when sending an email or launching an email campaign it s not just about creating pithy copy and an enticing subject line with or without an emoji you also need to ensure that your email communications are accessible to everyone on your database to drive engagement but to also ensure inclusivity creating accessible emails is about more than compliance it helps ensure every subscriber can read understand and engage with your campaigns regardless of device ability or assistive technology it can also help you deliver stronger email performance by improving usability readability engagement and deliverability tagged email marketing customer experience web design cro and ux share this share on x opens in new window x share on facebook opens in new window facebook email a link to a friend opens in new window email share on linkedin opens in new window linkedin share on whatsapp opens in new window whatsapp share on mastodon opens in new window mastodon share on nextdoor opens in new window nextdoor print opens in new window print share on reddit opens in new window reddit share on tumblr opens in new window tumblr share on pinterest opens in new window pinterest like loading ellisassociatesinc uncategorized leave a comment june 13 2026 13 minutes building brand authority that ai systems recognize and reference introduction ai systems do not rank brands these systems build a picture of what a brand is who it serves and how credible it is based on consistent signals across many sources a brand without that entity footprint stays invisible in ai generated answers regardless of where it ranks on google here is what that looks like in practice a brand holds the no 1 spot on google for its category its domain authority is strong its pages are indexed and its traffic looks healthy then a potential customer asks chatgpt perplexity or google s ai overviews aio for the best solution in that category but the brand does not appear a competitor with fewer backlinks and half the traffic gets named instead ai systems read it as a more credible consistently described entity this is the authority gap and it is one of the central problems in ai brand visibility strategy today chatgpt commands over 900 million weekly users as of february 2026 ali 2026 aio has already reduced daily traffic to wikipedia by approximately 15 khosravi yoganarasimhan 2026 these facts show how quickly chatgpt and ai overviews brand visibility have become a business critical concern a strong search ranking does not carry over to ai generated answers the two systems use different criteria to decide what appears building brand authority for ai means satisfying two distinct systems each with its own strategy the first is training data authority the long term presence that a brand builds across the web scale datasets that ai models learn from the second is retrieval authority the signals that get a brand pulled into a live answer at query time by retrieval augmented generation rag systems these two tracks form the framework for this article before the brand ranks no 1 on google after a buyer asks chatgpt the brand ranks no 1 on google the brand does not appear strong domain authority absent from chatgpt answers pages fully indexed absent from perplexity answers healthy organic traffic absent from google ai overviews traditional search visibility strong ai search visibility none ai systems don t rank brands they resolve them as entities a query typed into chatgpt perplexity or aio does not trigger a ranked list of websites the system instead draws on two separate processes the first is what the llm already learned from its training data built from billions of web pages articles and databases the second process is rag which pulls live sources at query time to add fresh specific information to the answer together these two processes determine what is included in an ai generated answer a brand that lacks presence in both is left out entirely this creates two questions every brand needs to answer does the ai system have a clear stable picture of the brand from its training data does the brand appear in the sources the retrieval layer currently checks the standard for being included looks less like a backlink profile and more like wikipedia s notability standard a brand needs repeated consistent mentions across independent and credible sources thin third party coverage scattered descriptions and contradictory positioning across platforms produce a weak entity signal giving an ai model no reliable picture to work from this is where generative engine optimization geo begins aggarwal et al introduced the core academic framework for this field in their princeton geo generative engine optimization paper their research showed that adding citations quotations and statistics to content produced a 30 40 improvement in visibility within ai generated answers aggarwal et al 2023 entity authority for ai is built through verifiable signals and evidence the rules that determined rankings in classic search engine optimization seo do not transfer directly to ai systems brand signals for ai search follow a different logic entirely geography adds a further layer u s developed models such as gemini and gpt show a marked entity perception bias with preferences for u s based entities regularly exceeding their global market share e g 9 out of 10 getaway city recommendations are u s based rienecker et al 2026 for non u s brands this means the bar is structurally higher more earned media more authoritative co mentions and stronger entity definition are all needed to compete the built in geographic bias toward u s headquartered entities is a documented measurable factor in llm brand recognition the bigger shift is in how search itself works ai search infers intent and synthesizes answers from multiple sources into a unified narrative response moving away from matching keywords to documents chen et al 2025 whether a brand appears in that response depends entirely on how well defined consistent and credible its entity profile is across the sources the model draws from classic seo signals ai system signals backlink volume and domain authority frequency of authoritative third party mentions keyword placement and density consistent brand description across sources page rank and serp position entity presence in knowledge graphs and structured databases click through rate signals co occurrence with credible topic relevant entities technical site performance schema markup and machine readable identity data content freshness for crawlers retrieval layer presence in rag indexed sources why getting cited by ai is actually two problems not one most brands treat ai visibility as a single challenge however being cited by ai presents two distinct problems training data authority and retrieval authority each requires a different strategy a different timeline and a different set of tactics solving only one produces incomplete results training data authority training data authority is how well a brand is represented inside an ai system s knowledge base llms such as gpt and gemini learn from web scale datasets including common crawl wikipedia major editorial publications and structured databases a brand that appears consistently across these sources is encoded as a credible entity new brands take a long time to accumulate the volume of consistent third party mentions needed to register as credible entities in model training data a brand earns that presence through sustained volume editorial features wikipedia inclusion structured database listings and repeated brand co occurrence in ai answers across authoritative sources this will take multiple years with no shortcuts a brand with strong training data authority gets surfaced even when the model runs without live retrieval retrieval authority retrieval authority is about what the ai model finds in real time when a question is asked rag based systems such as perplexity chatgpt search and google s aio pull live sources at query time to supplement the ai model s knowledge the question is whether the brand appears in the specific sources the retrieval layer checks right now ai search systems have a systematic and overwhelming bias toward earned media over brand owned content and social media posts earned media includes third party reviews and independent publications chen et al 2025 a brand s own website and press releases carry less weight during retrieval decisions than independent sources electronic word of mouth ewom becomes a direct brand authority geo asset digital channels amplify ewom through ai based algorithms expanding reach beyond the usual word of mouth theodorakopoulos et al 2025 for example a g2 review posted three years ago still feeds into...
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