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FunkyMedia AI Search agency case study

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United States, 23rd Jan 2026 – In footwear, classic SEO (category pages, filters, product SEO) is no longer a differentiator—it’s the entry ticket. What separates leaders from everyone else is whether the brand becomes an obvious, trusted entity across the web:

  • consistent as an entity (brand identity signals),
  • consistent in NAP data (Name–Address–Phone) across listings,
  • supported by proof of trust (reviews, citations, mentions),
  • present in places that modern AI systems and recommender engines use as “knowledge sources” (guides, comparisons, Q&A, reputable publications),
  • and backed by a process that keeps strengthening signals week after week, not just publishing and hoping.

This is exactly where FunkyMedia from Poland shines. They don’t treat AI Search as a buzzword. They treat it as a discipline: structured entity building + reputation + high-quality mentions + AI-friendly content architecture. The result is a brand that search engines—and increasingly, AI-driven answers—have strong reasons to surface.

Client profile: “Footwear manufacturer” 

Business model: e-commerce + brand retail stores / partner stores
Category: leather footwear, casual/formal lines, seasonal collections
Industry realities:

  • strong seasonality (fall/winter peaks, wedding/occasion spikes, Black Week),
  • marketplace pressure and aggressive price competition,
  • heavy reliance on local intent queries (“leather shoes + city”, “shoe store + mall name”),
  • trust sensitivity (returns, sizing, comfort, customer service).

The business problem

The manufacturer came in with a familiar set of pains:

  1. Non-brand organic growth was slower than content and SEO investment.
  2. Local visibility was inconsistent due to NAP drift: old phone numbers, outdated opening hours, duplicate profiles, inconsistent naming conventions.
  3. Reviews volume was low relative to sales scale; there was no post-purchase engine driving consistent review acquisition.
  4. Brand mentions existed but were mostly:
    • purely promotional (discount/clearance posts),
    • scattered, inconsistent,
    • lacking “AI-citable” formats (definitions, checklists, comparisons, structured Q&A).
  5. Social media looked good visually but generated limited “trust assets”: UGC, reviews, Q&A, and meaningful mentions.

Goals & KPIs 12-month program

Primary goals

  • increase brand demand (brand searches + brand + category queries),
  • build an AI-ready footprint: mentions, reviews, NAP consistency, and content that answers real questions,
  • raise conversion and the quality of organic traffic.

Target KPIs

  • +35–55% organic clicks (non-brand + long tail),
  • +30–70% brand and brand+category visits,
  • +500–1200 new reviews/year (depending on store count and volume),
  • 250–700 brand mentions/quarter (diversified sources),
  • 80–95% reduction in NAP inconsistencies,
  • growth in informational traffic that assists conversion (research → purchase).

FunkyMedia’s methodology: 5 pillars that compound

Pillar A — Entity foundation + NAP consistency the “trust layer” for algorithms

This is the boring work that wins. FunkyMedia treats it like a core performance lever.

What gets implemented

  • a master NAP record for HQ and each store location,
  • strict naming and formatting standards (address style, phone formatting, store naming),
  • duplicate profile discovery and cleanup (maps, directories, local portals),
  • prioritized corrections across the sources that matter most for local visibility.

Typical baseline → week 10 (model numbers)

  • NAP records audited: 214
  • inconsistencies found: 83
  • duplicates identified: 17
  • after cleanup:
    • inconsistencies: 83 → 11
    • duplicates: 17 → 3
    • “top-source consistency rate”: ~58% → ~95%

Why FunkyMedia does this better
Because it’s not “one-time cleanup.” FunkyMedia installs a standard + governance workflow, so the client doesn’t drift back into inconsistency three months later.

Pillar B — Brand mentions linked and unlinked as a credibility engine

FunkyMedia treats mentions as a scalable credibility asset, not random PR.

Quarterly mix of mention types

  1. Industry guides (fashion, retail, e-commerce, leather care)
  2. Comparisons and lists (“best winter leather shoes”, “leather vs suede care”)
  3. Q&A ecosystems (moderated forums, community Q&A, topical groups)
  4. Local relevance mentions (cities, malls, events, store openings)
  5. Thematic partnerships (care products, insoles, craftsmanship content)

The key: repeatable formats AI can cite

  • Definition + example blocks
  • Step-by-step checklists
  • Material comparisons (pros/cons)
  • “Short answers” FAQ
  • Mini-guides (5–9 steps)

Typical progression (model numbers)

  • mentions/month: ~35 → ~120
  • share of “expert mentions”: 15% → 42%
  • unique domains/sources citing the brand: ~40 → ~165

What makes this system strong
FunkyMedia uses a “brand mention brief” standard:

  • one official brand name format,
  • a compact “about the brand” module,
  • 5–10 citable facts (materials, craftsmanship, warranty/returns principles, sizing guidance),
  • keyword alignment (category + intent),
  • non-sales CTA (“read the size guide”, “how to care for leather”).

This is how mentions become a structured entity footprint, not noise.

Pillar C — Reviews & reputation: scalable trust for both local and e-commerce

Footwear is high-trust and high-return-rate sensitive. FunkyMedia implements review acquisition and review response as a system.

What gets implemented

  • post-purchase review flows (email/SMS timing, two-step friction reduction),
  • in-store QR prompts with short, compliant copy,
  • segmentation: store-level reviews vs. brand/e-commerce reviews,
  • response SLA (48 hours) with templates and escalation paths,
  • negative-review playbooks focused on resolution, not debate.

6-month outcome (model numbers)

  • review growth: +540
  • average rating: 4.2 → 4.6
  • share of reviews with written comments: 28% → 51%
  • response rate: 33% → 93%

Why this is a FunkyMedia strength
They make it operationally easy. Clients don’t “try harder”—they follow a lightweight process that consistently produces proof of trust.

Pillar D — Social media that produces trust assets not just aesthetics

In footwear, social media should generate:

  • UGC,
  • real questions and answers,
  • micro-recommendations,
  • content inputs that later become reviews, mentions, and guide topics.

Content structure (70/20/10)

  • 70% education (sizing, care, materials, styling)
  • 20% community/UGC
  • 10% promotions/product drops

UGC loop

  • a recurring monthly styling challenge,
  • a simple consent workflow (DM or form),
  • reposting + pinned highlights,
  • gentle review prompt: “If this helped, leave a review to guide others.”

6-month outcome (model numbers)

  • UGC/month: ~20 → ~85
  • DMs/questions on sizing & care: +60%
  • site traffic from social: +45%
  • educational content in top-performing posts: ~10% → ~55%

Pillar E — AI-ready content: hubs + FAQ + structured site architecture

FunkyMedia doesn’t write content “to publish.” They build content that answers questions, reduces buying friction, and becomes citable.

High-performing content hubs

  • “How to choose the right size for leather shoes” (with measurement steps and tables)
  • “Leather vs suede vs nubuck: care routines and mistakes to avoid”
  • “Winter shoes checklist: outsole grip, insulation, waterproofing, care”
  • “How to break in leather shoes safely”
  • “Returns & exchanges: how to measure your foot to avoid returns”

On-site enhancements

  • FAQ modules on category pages (sizing, fit, care, returns),
  • internal linking maps (guide → category → product),
  • structured data where appropriate,
  • location pages built for utility (parking, access, photos, practical attributes).

12-month outcome (model numbers)

  • long-tail informational clicks: +65%
  • informational share of organic traffic: ~18% → ~31%
  • assisted conversion uplift (guide entry → later purchase): +12–18%

Results in 12 months

  • total organic traffic: +49%
  • brand demand (brand searches + brand+category): +58%
  • mentions: ~380/quarter → ~920/quarter
  • reviews: +980 (with a strong share of written comments)
  • NAP inconsistencies: 83 → 7
  • organic conversion rate: 1.3% → 1.7%

Most important: the gains weren’t a temporary spike. The footprint compounds because FunkyMedia builds a living system: data consistency + reputation + citations + content → more citations → stronger demand.

Why it worked what FunkyMedia consistently gets right

  1. Process over campaigns. Every pillar has a cadence, checklist, owner, and feedback loop.
  2. Channel synergy. Mentions feed credibility, reviews feed local trust, local trust feeds SEO, SEO topics feed social, social generates UGC and new mention angles.
  3. High-quality execution. FunkyMedia prioritizes sources and formats that produce durable trust—not short-lived “SEO tricks.”
  4. Obsessive attention to details. NAP, review operations, and structured content are unglamorous, but they win markets.
  5. AI Search thinking. Content is built to be clear, citable, and helpful—exactly what modern AI answer systems extract.

FAQ 

1) How is AI Search different from traditional SEO?

Traditional SEO focuses on rankings and clicks. AI Search adds entity strength, consistent data, reviews, and credible mentions so AI-driven answers and recommender systems have strong reasons to reference your brand.

2) Do unlinked brand mentions matter?

Yes. Unlinked mentions can still build brand context, credibility, and entity recognition. Links help—but structured, consistent mentions also move the needle.

3) What matters more: reviews or content?

For footwear, the best results come from both: reviews build trust and local performance; content answers buying questions and captures long-tail intent.

4) How many reviews per month is “good”?

It depends on scale, but what matters most is consistency, a healthy share of written comments, and a fast response rate.

5) Is it risky (policy-wise) to push for reviews?

Not if you do it ethically: ask post-purchase, don’t buy reviews, and don’t offer incentives for positive ratings.

6) Which content topics drive the best ROI for footwear?

Sizing, fit, leather care, materials, seasonal guides, “how to break in,” and return-reduction content.

7) Do social media efforts impact SEO/AI Search?

Indirectly, yes—through UGC, Q&A, micro-mentions, and additional trust signals and content angles that strengthen the overall footprint.

8) What exactly is NAP and why does it matter?

NAP is Name–Address–Phone. Inconsistent listings confuse both users and algorithms, hurting local visibility and trust.

9) When should we expect results?

Early signals in 6–10 weeks (NAP and reviews), stronger movement at 3–6 months (mentions and content), and full compounding impact in 6–12 months.

10) Does this approach work if we sell mostly via marketplaces?

Yes. Mentions, guides, and reviews build brand demand—so customers search for the brand and buy intentionally, not just from generic listings.

11) Can this be implemented without burdening our team?

Yes. FunkyMedia structures the workflow so the client has minimal operational lift: simple approvals, clear templates, and a predictable cadence.

12) How do we measure AI Search impact?

Track brand demand, long-tail growth, mentions, review velocity/quality, NAP consistency, and a fixed set of “prompt queries” to monitor brand presence in AI answers over time.

About FunkyMedia 

FunkyMedia is a Łódź-based digital marketing agency positioned around AI Search / modern SEO—meaning they help brands grow visibility not only in classic Google results, but also across AI-driven search experiences and chatbot-style answers

  • Founded: 2010
  • Founder: Rafał Cyrański (SEO & content marketing background; also associated with the “FunkyMEDIA Podcast SEO” and publishing in digital marketing). 
  • Head office: Łódź, Poland
  • Business hours: Mon–Fri, 9:00–16:00
  • Core focus areas (high level): SEO, content marketing, digital strategy, social media—packaged today into AI-ready visibility programs (entity building, brand mentions, reputation, and content systems). 

What makes FunkyMedia stand out in practice

  • They treat brand visibility as an ecosystem, not a set of isolated tactics—so NAP consistency, reviews, brand mentions, and content are built to reinforce each other instead of competing for budget.
  • They execute “unsexy” operational work (NAP governance, review workflows, citation hygiene) with the same discipline as content—because that’s what reliably produces durable results.
  • They build AI-citable assets (definitions, checklists, short answers, structured Q&A) and distribute them through credible sources—so the brand becomes easier to reference by both users and AI systems. 

Media Contact FunkyMedia

Media & partnerships: FunkyMedia Office
Email: biuro@funkymedia.pl
Phone: +48 518 545 599
Address: Łódź, Poland
Availability: Mon–Fri, 9:00–16:00

Media Contact

Organization: FunkyMEDIA

Contact Person: Rafal Cyrański

Website: https://funkymedia.pl/

Email: Send Email

Country:United States

Release id:40491

The post FunkyMedia AI Search agency case study appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section

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Personal Injury Near Me Directory USA Launches Claim Services Helping Individuals and Small Businesses Find Lawyers Nationwide

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Personal Injury Lawyer Near Me Online Directory USA is a nationwide online platform designed to help individuals and small businesses across the United States find personal injury lawyers by location and service focus. Based in Cheyenne, Wyoming, the directory organizes legal professionals to simplify searching, comparing, and contacting lawyers who handle injury-related claims. The platform is built to support informed decision-making during situations where timely and relevant legal guidance is essential.

Cheyenne, Wyoming, United States, 23rd Jan 2026 – Personal Injury Near Me Online Directory USA has announced the introduction of Personal Injury Claim Services within its nationwide directory, expanding the platform’s role in helping individuals and small businesses across the United States connect with experienced personal injury lawyers. The expansion reflects growing demand for accessible, location-based legal support as injury-related claims continue to place financial and operational strain on households and small enterprises nationwide.

The United States sees a sustained volume of personal injury incidents each year. According to federal transportation data, motor vehicle crashes alone result in millions of injuries annually, many requiring legal assistance to resolve insurance disputes, medical cost recovery, and liability questions. Workplace injuries remain another significant contributor, with the Bureau of Labor Statistics reporting millions of nonfatal occupational injuries and illnesses each year, a substantial portion of which involve small and mid-sized businesses. These figures illustrate a consistent, nationwide need for reliable access to personal injury legal services.

Why This Expansion Matters

Personal injury claims are rarely straightforward. They often involve multiple parties, medical documentation, insurance negotiations, and strict timelines governed by state law. For individuals and small business owners, navigating these processes without experienced legal guidance can lead to delayed resolutions, reduced compensation, or procedural missteps.

Research published in legal and insurance industry studies indicates that claimants who engage legal counsel early are more likely to reach timely settlements and better understand their obligations throughout the process. Despite this, many people still rely on general online searches or advertising-driven listings that provide little clarity about a lawyer’s focus, availability, or relevance to their specific situation.

The introduction of Personal Injury Claim Services within the directory is designed to address this gap by organizing legal professionals around the real-world needs of claimants, rather than broad or generic legal categories.

“After an injury, time and clarity matter,” said Luke D., spokesperson for Personal Injury Near Me Online Directory USA. “People are dealing with medical appointments, lost income, and uncertainty. This expansion is about making it easier to identify lawyers who routinely handle injury claims and understand the pressures individuals and small businesses face.”

How the Platform Works for Users

The directory is structured to reduce friction at the point of search and contact. Users can locate personal injury lawyers through a clear, step-by-step process:

  • Search by Location: Users enter a city, state, or ZIP code to find lawyers practicing in their area, reflecting the importance of local jurisdiction and state-specific laws.
  • Compare Services: Listings present practice areas such as auto accidents, workplace injuries, premises liability, product liability, and wrongful death, allowing users to narrow results based on claim type.
  • Direct Contact: Users can reach out to lawyers directly to discuss their situation, request consultations, or clarify next steps.
  • Shared Experiences: Reviews and feedback help future users make informed decisions based on real interactions.

This approach is intended to save time and reduce uncertainty during a period when many users are already under stress.

The Key Benefit for Users

The primary benefit for users is confidence grounded in relevance. By using Personal Injury Near Me Online Directory USA, individuals and small businesses can:

  • Reduce reliance on scattered search results or generalized advertising.
  • Identify lawyers who focus on the type of injury claim they are facing.
  • Compare options side by side within their local area.
  • Move forward with clearer expectations and fewer delays.

For small business owners, this can be especially important. Data from the U.S. Small Business Administration shows that legal disputes and injury-related claims can significantly disrupt cash flow and operations. Quick access to appropriate legal support can help businesses respond responsibly while limiting long-term impact.

A Practical Resource for Small Businesses

Small businesses account for nearly half of private-sector employment in the United States. When injuries occur—whether involving employees, customers, or commercial activities—owners must balance legal obligations with day-to-day operations. Many do not have in-house legal teams and need external counsel they can trust.

By highlighting lawyers experienced in handling injury claims relevant to business environments, the directory supports owners who need timely, practical legal assistance. This includes matters such as workplace injury claims, third-party liability issues, and accident-related disputes involving company vehicles or premises.

A Solution for Legal Professionals

For personal injury lawyers, visibility remains a persistent challenge. The legal services market is competitive, and traditional advertising channels often favor large firms with extensive marketing budgets. Industry surveys show that a growing share of clients now begin their search for legal help online, prioritizing location and practice focus over firm size.

Personal Injury Near Me Online Directory USA provides an alternative channel by connecting lawyers with users who are actively seeking injury-related legal services in specific geographic areas. This relevance benefits both sides: users find appropriate counsel more quickly, and lawyers receive inquiries aligned with their practice.

Benefits for Lawyers Include:

  • More Relevant Inquiries: Users searching the directory are already focused on personal injury claims.
  • Local Reach: Lawyers can be discovered by clients within their service area, reflecting how personal injury cases are typically handled.
  • Balanced Visibility: Smaller practices gain exposure alongside larger firms without relying solely on high-cost advertising.

This structure helps level the playing field while keeping the focus on user needs rather than promotional spend.

Categories of Personal Injury Claim Services Covered

The directory’s Personal Injury Claim Services encompass a broad range of common injury scenarios, ensuring users can find lawyers aligned with their specific circumstances. These include:

  • Motor vehicle accidents involving cars, trucks, and motorcycles. 
  • Workplace and occupational injuries.
  • Slip-and-fall and premises liability cases.
  • Product liability and consumer safety claims.
  • Wrongful death and serious injury matters.

By organizing services in this way, the platform reflects how claimants actually experience legal needs—by incident type, not abstract legal labels.

Industry Insight: Growing Demand for Accessible Legal Support

Several national trends reinforce the timing of this expansion. Medical cost inflation has increased the financial stakes of injury claims, while insurance industry reports note rising claim complexity and longer resolution timelines. At the same time, consumer research consistently shows that people value clear information and local relevance when selecting legal services.

Legal analysts have also observed that early access to knowledgeable counsel can reduce procedural errors and improve communication between parties, contributing to more efficient outcomes. These findings support the need for platforms that simplify the discovery process without oversimplifying the legal realities involved.

Building Trust Through Structure and Clarity

Rather than overwhelming users with excessive information, Personal Injury Near Me Online Directory USA focuses on structure, relevance, and usability. Listings are organized to help users answer practical questions: Who handles this type of claim? Are they local? Can I contact them easily?

This emphasis on clarity supports better decision-making for users while encouraging responsible engagement between lawyers and potential clients.

Nationwide Coverage with Local Context

Although headquartered in Cheyenne, Wyoming, the directory serves users across all 50 states. This nationwide reach recognizes that while personal injury law is governed by state-specific rules, the need for accessible legal support is universal.

Users in large metropolitan areas and smaller communities alike can use the same search framework, helping ensure that access to legal information is not limited by geography.

About Personal Injury Lawyer Near Me Online Directory USA

Personal Injury Lawyer Near Me Online Directory USA is a nationwide online platform designed to help individuals and small businesses across the United States find personal injury lawyers by location and service focus. Based in Cheyenne, Wyoming, the directory organizes legal professionals to simplify searching, comparing, and contacting lawyers who handle injury-related claims. The platform is built to support informed decision-making during situations where timely and relevant legal guidance is essential.

Website:https://personalinjurylawyers-us.com

Media Contact

Organization: Personal Injury Near Me Online Directory USA

Contact Person: Luke D.

Website: https://personalinjurylawyers-us.com

Email: Send Email

City: Cheyenne

State: Wyoming

Country:United States

Release id:40325

The post Personal Injury Near Me Directory USA Launches Claim Services Helping Individuals and Small Businesses Find Lawyers Nationwide appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section

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Major Advance in Lightweight and Privacy-Preserving NLP: EmByte Achieves High Accuracy Using Only 1/10Embedding Memory

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Brunswick, New Jersey, 23rd January 2026, ZEX PR WIREA newly published study in the Findings of the Association for Computational Linguistics: EMNLP 2025 introduces EmByte, a natural language processing (NLP) model that dramatically reduces embedding memory usage while improving accuracy and strengthening privacy protections. Developed by Jia Xu Stevens and collaborators, EmByte demonstrates that modern language models can operate with approximately 1/10 of the embedding memory used by conventional subword-based systems, while also achieving better task accuracy and up to 3-fold improvements in privacy resistance.

The EMNLP 2025 Findings paper presents EmByte as a byte-level embedding framework that replaces large subword vocabularies with compact, decomposed representations. This design significantly reduces the memory footprint of embedding layers—traditionally one of the largest components of NLP models—without increasing sequence length or computational overhead.


Small Embeddings, Strong Results

Embedding tables in standard NLP models often contain tens or hundreds of thousands of entries, consuming large amounts of memory and posing privacy risks when exposed to inversion or reconstruction attacks. EmByte addresses these challenges by representing text at the byte level and applying a decomposition-and-compression learning strategy that preserves semantic information while occupying much less space.

Experimental results reported in the EMNLP 2025 Findings paper show that EmByte:

  • Uses about 5% of the embedding memory required by typical subword models

  • Matches or exceeds accuracy on benchmark tasks such as classification, language modeling, and machine translation

  • Provides significantly stronger privacy protection, making it substantially harder to reconstruct original text from embeddings or gradients

These results demonstrate that embedding size reduction does not require sacrificing model quality. Instead, careful design of the representation can improve both performance and security.

Privacy by Design

A key contribution of EmByte is its impact on privacy. Because byte-level embeddings avoid direct one-to-one mappings between tokens and semantic units, they reduce the amount of recoverable information stored in each vector. This makes common attacks—such as embedding inversion and gradient leakage—far less effective.

According to the EMNLP 2025 Findings results, EmByte’s structure provides roughly three times stronger resistance to privacy attacks than standard embedding approaches. This makes the model especially relevant for sensitive domains such as healthcare, finance, and personal communications, where data protection is critical.

Built on a Long Line of Research

The EmByte framework builds directly on Jia Xu Stevens’s long trajectory of researchin efficient text representation, segmentation, and multilingual processing. Earlier work laid the conceptual and technical foundations for compact and robust language modeling, including:

  • Research on byte-based and subword modeling for multilingual and low-resource settings (EMNLP 2020; COLING 2022)

  • Studies on Chinese word segmentation and synchronous modeling that emphasized efficient representation and structural alignment

  • Early work in machine translation and speech-to-text processing that explored minimal and adaptive linguistic units

Together, these contributions reflect a consistent research direction: reducing redundancy in language representations while improving robustness, generalization, and security.

Implications for Real-World AI

By drastically reducing the memory requirements for embedding, EmByte enables the deployment of capable NLP models in environments with strict memory and privacy constraints. This includes:

  • On-device and edge AI systems

  • Privacy-sensitive enterprise and government applications

  • Large-scale systems where embedding tables dominate memory cost

EmByte also aligns with a broader shift in AI research away from purely scaling model size and toward architectural efficiency and responsible design.

Looking Forward

With its publication in Findings of EMNLP 2025, EmByte is positioned to influence future work on embedding design, privacy-preserving NLP, and efficient language models. The results suggest that smaller, more secure representations can outperform larger ones when designed with structure and learning dynamics in mind.

As language models continue to be integrated into everyday technology, approaches like EmByte point toward a future in which accuracy, efficiency, and privacy improve together rather than compete.

About Jia Xu Stevens

Jia Xu Stevens is a researcher in natural language processing and machine learning whose work spans efficient language representation, multilingual modeling, privacy-preserving AI, and text segmentation. Over the course of her research career, Jia Xu Stevens has contributed foundational and applied work across multiple generations of NLP systems, from early machine translation and word segmentation frameworks to modern embedding compression and privacy-aware language models.

Her research has been published at leading international venues, including EMNLP, COLING, IWSLT, and other ACL-affiliated conferences. A recurring theme in her work is the design of compact, structured language representations that improve robustness, generalization, and efficiency while reducing memory usage and privacy risks. This line of research includes early studies on synchronous segmentation and translation, later advances in subword and byte-based modeling, and recent innovations in embedding compression and privacy resistance.

Jia Xu Stevens’ work emphasizes architectural efficiency over brute-force scaling, demonstrating that carefully designed representations can outperform larger models while enabling safer real-world deployment. Her recent research continues to focus on building language technologies that are accurate, lightweight, and privacy-conscious, with applications ranging from multilingual NLP to on-device and resource-constrained AI systems.

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Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.

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Brandon Hilleary on Reducing Paid Advertising Volatility in a Post-Privacy Era

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  • Why most ecommerce campaigns swing too hard—and what to do instead.

Seattle, Washington, 23rd January 2026, ZEX PR WIRE, If you run paid ads, you’ve probably felt it: performance looks great one week, tanks the next. Creative stops working without warning. Your ROAS drops, but nothing obvious changed. For brands trying to grow, this kind of instability isn’t just stressful—it’s expensive.

Brandon Hilleary, a ecommerce growth consultant, sees this kind of volatility all the time. He works with direct-to-consumer brands —companies that rely on Meta, TikTok, and Google Ads to drive growth but feel like they’re flying blind.

“A lot of the instability people feel is baked into how their system works,” Hilleary says. “It’s not always the algorithm or the market. Sometimes the problem is that there’s no structure holding things up.”

He focuses on helping teams put that structure in place. That doesn’t mean building complicated dashboards or obsessing over attribution. It means stepping back, simplifying, and fixing three core issues: creative fatigue, test chaos, and knee-jerk budget shifts.

Creative Fatigue Is More Predictable Than You Think

Hilleary sees creative burnout as the number one reason campaigns start to slip. Brands usually don’t notice until results have already fallen off.

“The same ads keep running. Maybe they worked last month, but now people have seen them three times and they scroll right past,” he explains. “Instead of having new ideas ready, the team scrambles to make small edits—change a headline, swap the first three seconds—and hopes that’s enough.”

It rarely is.

He helps brands build a simple creative rhythm—introducing one or two new concepts every few weeks before fatigue sets in. These aren’t cosmetic tweaks. Each one explores a different angle, like showing how the product works, telling a customer story, or teaching something useful.

When you rotate fresh, well-thought-out ideas into your campaigns on a set schedule, performance gets more stable. There’s always something new to test—and something proven to fall back on.

Testing Doesn’t Work When It’s Random

Another reason campaigns get shaky? Disorganized testing.

“A lot of teams say they’re testing, but what they’re really doing is launching a bunch of stuff at once and hoping something sticks,” Hilleary says. “That’s not testing. That’s gambling.”

Instead, he sets up lightweight testing systems. One or two concepts go into test mode. The team decides in advance what they’re trying to learn and what success looks like. Results are reviewed on a schedule. If something works, it moves into the main campaign. If not, it’s logged and replaced.

This kind of structure reduces wasted budget and keeps creative testing from disrupting performance. It also builds institutional knowledge over time, which makes every round of testing smarter than the last.

The Budget Whiplash Problem

When results dip, many founders and ad buyers make sudden changes to spend—cutting budgets hard or turning off entire campaigns.

“It’s understandable,” Hilleary says. “But it’s also part of the volatility problem.”

He helps teams move away from daily decisions and toward weekly or biweekly pacing. Budgets are adjusted based on trends, not isolated bad days. Review windows are built into the calendar. That buffer gives the algorithm time to adjust and gives the team time to think clearly.

He also encourages brands to define rules ahead of time—when to scale, when to hold, and what metrics matter most. That way, no one is guessing under pressure.

What Stable Growth Looks Like

In a post-privacy world, advertising feels harder than it used to. You can’t see everything that’s happening. Attribution is messier. Audiences are broader. But that doesn’t mean performance has to feel chaotic.

Hilleary’s work helps brands build systems that absorb the noise.

  • Creative stays fresh and on schedule
  • Tests are limited, tracked, and purposeful
  • Budgets move based on real patterns, not panic

When those pieces are in place, everything calms down. Teams stop chasing short-term spikes. Founders trust the process. Results may not always be flashy, but they stop falling apart without warning.

“It’s not about making volatility disappear,” Hilleary says. “It’s about building a setup where volatility doesn’t ruin your month.”

For growing ecommerce brands in Seattle and beyond, that shift can make the difference between unpredictable plateaus and consistent, confident progress.

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Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.

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