DMi Partners Blog

How to Evaluate a TikTok Shop Agency: 8 Things Brands Should Consider

Kristina Nolan — 2026-09-28T10:01:35+00:00

TikTok Shop has quickly become one of the most talked about opportunities in social commerce. And as more brands look to capitalize on its growth, there has been an equally rapid rise in agencies claiming to be TikTok Shop experts.

TikTok Shop isn’t simply another paid social channel, an influencer campaign, or an affiliate program. Success requires a combination of creator recruitment, affiliate strategy, content development, commission and incentive management, paid amplification, merchandising, promotional planning, and ongoing optimization.

For brands evaluating a TikTok Shop agency, knowing what to avoid can be just as important as knowing what to look for. Here are eight red flags that may signal a TikTok Shop partner isn’t equipped to help your brand build sustainable growth.

1. They Guarantee a Specific Level of GMV

If a TikTok Shop agency guarantees that your brand will generate a certain amount of GMV (Gross Merchandise Value) within a specific timeframe, proceed carefully. TikTok Shop performance is influenced by dozens of variables, including product market fit, pricing, promotional strategy, creator adoption, content quality, inventory, commission rates, category demand, seasonality, and TikTok’s algorithm.

An experienced agency should be able to establish performance benchmarks and create a roadmap for growth, but those projections should be grounded in assumptions, not presented as guarantees.

What to look for instead: A partner that can explain the inputs behind its projections, establish realistic milestones, and show you how its strategy will evolve based on actual performance data.

2. Their Entire Strategy Is Centered Around Sampling

Product seeding is an important component of TikTok Shop affiliate marketing. But sending thousands of samples isn’t a strategy by itself. The real question is what happens after the sample is approved. How is the agency determining which creators should receive product? What percentage of sampled creators are posting content? How many times do they post? Which creator profiles are producing revenue? What content hooks are converting? And how are those insights being used to improve the next wave of recruitment?

A program can have impressive outreach and sampling numbers while producing very little meaningful revenue.

What to look for instead: A TikTok Shop agency that measures the entire creator funnel from outreach and sample approval to posting rate, content volume, GMV, and repeat performance.

3. They Focus on Follower Count More Than Creator Performance

On TikTok Shop, the creator with 25,000 followers can sometimes dramatically outperform the creator with 2 million. Follower count can provide useful context, but it shouldn’t be the primary metric used to determine which creators receive attention, samples, higher commissions, or additional incentives. Commerce content behaves differently from traditional influencer marketing. A creator’s ability to demonstrate a product, establish credibility, develop an effective hook, and motivate someone to purchase can matter significantly more than audience size alone.

What to look for instead: An agency that evaluates creators based on commerce specific signals such as historical GMV, posting frequency, video level performance, category relevance, conversion behavior, and repeatability.

4. They Can’t Explain Their Content Testing Strategy

TikTok Shop is ultimately powered by content, which means your agency should have a clear answer when you ask: “How are you figuring out which content truly sells our product best?” If the response is “we let creators be authentic,” that may not be enough. Creator authenticity is important, but the strongest TikTok Shop programs learn systematically from what works.

Agencies should be identifying patterns across hooks, formats, product demonstrations, pain points, calls to action, creator archetypes, and offers. For example, does transformation content outperform product education? Do problem solution hooks drive stronger engagement? Are videos featuring a particular use case generating higher conversion rates? Does one creator vertical consistently outperform another?

Those learnings should inform future creator briefs, recruitment, paid amplification, and testing.

What to look for instead: A partner with a structured testing methodology and a process for turning successful creative patterns into repeatable insights without making every creator’s content feel scripted.

5. They Treat TikTok Shop Like Traditional Influencer Marketing

One-off creator activations can generate awareness, but TikTok Shop requires a different operating model. Brands aren’t merely paying creators to publish a predetermined number of posts. The goal, rather, is to build an ecosystem of creators who have an economic incentive to keep producing content because that content continues generating sales. That changes how agencies should think about recruitment, creator relationships, commissions, incentives, content volume, and retention. A creator who generates $10,000 from one video may be valuable. A creator who repeatedly produces converting content and becomes a long-term advocate for the brand can be even more valuable.

What to look for instead: A TikTok Shop agency that has experience with affiliate marketing and understands how to build ongoing, performance driven creator relationships, not just execute influencer campaign.

6. They Report Big Numbers Without Showing You the Funnel Behind Them

10,000 creators contacted. 2,000 samples sent. 500 videos generated. Those numbers may sound impressive, but volume without context can hide significant performance problems. If 2,000 products were sent and only 150 creators posted, that’s important. If hundreds of videos were generated but nearly all GMV came from three creators, that’s important too. Your TikTok Shop reporting should help you understand why performance is happening, not just how much activity occurred.

A strong reporting framework might include metrics such as creator outreach, sample acceptance, sample-to-post rate, videos per creator, active affiliates, GMV per creator, GMV per video, commission efficiency, top-performing creator segments, creative performance, and repeat creator activity.

What to look for instead: Reporting that connects agency activity to business outcomes and clearly identifies where the biggest opportunities and bottlenecks exist.

7. They Don’t Have a Plan for What Happens After Something Works

Getting a viral video is exciting, but building a repeatable system for producing more successful content is much more valuable. One of the biggest differences between a short-term TikTok Shop win and sustainable growth is what happens after a creator, video, hook, product, or offer starts performing. Does the agency immediately recruit more creators with similar profiles? Does it encourage the creator to publish additional variations? Does it identify what made the video successful? Does it test similar hooks with other creators? Does it evaluate whether the content should receive paid amplification?

A TikTok Shop agency shouldn’t only celebrate winners. It should also have a system for turning winners into a growth strategy.

What to look for instead: A clear process for identifying, analyzing, and scaling successful creators and creative concepts.

8. They Don’t Have Paid Media Expertise

TikTok Shop may be creator led, but the strongest programs don’t rely on organic affiliate content alone. When a creator produces content that converts, brands have an opportunity to put additional investment behind that content through paid media - extending its reach, accelerating sales, and generating additional data about which creative concepts and audiences are most effective. That’s why paid media expertise should be an important consideration when evaluating a TikTok Shop agency.

A partner that only manages creator recruitment and affiliate relationships may be able to identify potential winning content, but they may not have the expertise to determine when a piece of content is worth amplifying, how much to invest behind it, or how paid performance should influence the broader creator and content strategy.

Paid media shouldn’t operate as a separate workstream from your TikTok Shop program. The insights should move in both directions. High-performing affiliate content can inform paid creative strategy, while paid performance can reveal hooks, messages, products, and creator styles that should be replicated across the affiliate program.

What to look for instead: A TikTok Shop agency with hands on paid social expertise that can connect creator performance, creative testing, and media investment into one feedback loop: identifying effective content, amplifying it strategically, and using those learnings to make the entire program stronger.

The strongest TikTok Shop programs are built through continuous experimentation: recruiting the right creators, generating enough content to learn quickly, identifying what converts, reallocating resources toward what works, and repeating that process at greater scale. When evaluating a TikTok Shop management agency, look beyond promises of creator access, sampling volume, or viral content. Look for a partner that can clearly explain how they learn, how they measure performance, and how they turn those learnings into sustainable growth.

Journey Builder vs. Automation Studio: Where Logic Actually Belongs

Abby Deel — 2026-08-24T10:01:35+00:00

If you’ve spent any time in Salesforce Marketing Cloud, you’ve probably had this debate with your team: should this logic live in Journey Builder or Automation Studio?

It’s a valid question, as well as a common source of frustration. But the debate only exists because of a foundational misconception that these tools compete with each other. In reality, they just solve different problems.

In plain terms, logic is just the rules that drive decisions in your marketing program. Things like: Who should receive this email? Has it been seven days since someone made a purchase? Did they click the last message or not? Should this person get the promotional version or the loyalty version?

Those rules have to live somewhere in your email marketing platform, and where you put them matters more than most teams realize. Journey Builder orchestrates email marketing experiences. Automation Studio processes and prepares data. The real challenge isn’t which tool can handle a given rule; it’s figuring out where that rule belongs.

The Core Difference

Journey Builder is stateful. It tracks individual contacts, remembers where they are, and determines what happens next based on their behavior and attributes. It supports waits, decision splits, exit criteria, and goal tracking all at the customer level.

Automation Studio is stateless. It’s built for recurring campaigns where the logic itself doesn’t change often. Think campaigns like daily deals, weekly newsletters, or quarterly announcements. It executes processes in batches: running SQL queries, building audiences, importing files, and sending campaigns. It doesn’t track customer progression between runs, so tomorrow starts completely fresh.

A helpful way to think about it: Journey Builder remembers people whereas Automation Studio doesn’t.

One of the biggest misconceptions is that you can replicate a journey in Automation Studio by scheduling sequential sends to day-based audiences. Technically, yes. But what looks like a journey is actually just a series of batch sends. There’s no customer state, no exit logic, and no progression tracking. The customer experience might look similar on the surface, but the architecture underneath is completely different.

Where the Biggest Differences Appear

The table below breaks down how each tool handles the logic decisions teams face most often:

Capability	Journey Builder	Automation Studio
Decisioning & Branching	Visual decision splits; routes contacts by attributes or behavior; rules are evaluated top-down, first match wins.	SQL-driven segmentation; rules live in queries; no native branching, but handles unlimited complexity.
Audience Management	Admits contacts and maintains their state after entry; rule changes to the entry source only affect future entrants.	Rebuilds the audience on every execution based on current rules; no memory of previous runs.
Exit Criteria & Suppression	Configurable exit rules can remove contacts mid-journey; suppression can block sends, but the contact may still remain in the journey.	Exclusion rules apply at audience creation; ineligible contacts never enter the send in the first place. There is no way to pull someone out mid-flow unless the automation is manually stopped.
Reporting & Visibility	Path-level and goal-level reporting shows where customers drop off and which decision branches perform; version history lets you compare performance before and after a logic change.	Process-level reporting only monitors whether queries ran, failed, or timed out. There is no versioning, so if you change a wait delay or add or remove an email without renaming anything, you lose the ability to see how performance shifted after the change.
A/B & Path Testing	Native random-split and decision-split testing; Path Optimizer can automatically evaluate paths and roll out the winner.	No native A/B testing capability. There is no random-split or decision-split feature, so any testing must be built into the audience using queries.
Validation & Error Notification	Robust validation runs when you launch a new journey or journey version, catching issues such as data-extension mismatches or misconfigured logic before it goes live. Once live, Journey Builder will not alert you to errors, so you have to watch reporting closely.	No launch-time validation; you run it and see what happens. However, automations can be configured to send email alerts when something breaks, such as a failed send or query error.
AI & Advanced Functions	Supports Einstein Send Time Optimization, frequency and scoring splits, Path Optimizer, and a Wait Until function that holds a contact in the journey indefinitely until a specified date field meets the criteria.	No native AI functionality. Einstein prediction scores can still be used, but only by pulling them into a SQL query or filter to help build the audience manually.

A few things to be aware of:

Removing someone from an entry Data Extension does not remove them from an active journey.
A contact can unsubscribe, purchase, or become ineligible and still remain in a journey if exit logic isn’t configured.
Journey Data is a snapshot taken at entry and doesn’t update as the journey progresses. If a query is used for the entry source of the journey DE and that query is updated, the changes will only affect new data entering the journey.

The Architecture Most Mature Teams Use

The teams that get the most out of SFMC don’t pick one tool over the other. They use both, with a clear separation of responsibilities.

Automation Studio handles the data processing layer: imports, cleansing, scoring, segmentation, and audience preparation. Journey Builder handles the customer experience layer: messaging, timing, personalization, branching, and exit management.

The flow looks like this:

Source Systems → Automation Studio (Data Preparation) → Prepared Audience → Journey Builder (Customer Experience)

This keeps complex business logic centralized in SQL, where it’s easier to maintain and update. And it keeps email marketing journeys clean, readable, and measurable without burying logic in places marketers can’t see or adjust.

How to Decide: A Quick Framework

When you’re scoping new logic, the question to ask is: does this determine who qualifies, or does it determine what happens next?

Use Journey Builder when:

Customer state and timing matter
You need behavioral branching
Reporting on path performance is important
You need exit criteria or lifecycle management
A/B testing is part of the strategy

Scenario 1: Winback Journey

A Winback Journey is well suited for Journey Builder when customers need individualized timing, behavioral branching, and exit criteria based on engagement or purchase activity. Journey Builder provides visual decision splits to route contacts based on their attributes or behavior, while path-level reporting shows where customers drop off and which branches perform best. It also supports native A/B and path testing, making it easier to test different winback strategies and optimize the customer experience over time.

Use Automation Studio when:

You’re processing or preparing data
Your audience needs to rebuild daily based on fresh criteria
The logic is SQL-driven and batch-based
You need easy operational control

Scenario 2: Newsletter Campaign

A newsletter is well suited for Automation Studio when emails are sent on a consistent schedule, and the campaign can be reused from month to month, with content updated as needed. Automation Studio rebuilds the audience based on the current segmentation rules with each run, making it a good fit for recurring campaigns where audience state changes. It also avoids the need to version up a journey whenever an email is updated and can be configured to send email alerts when a query, send, or other automation step fails.

Use both together when:

You’re building scalable lifecycle marketing
You want a clear separation between data logic and customer experience

The most scalable SFMC implementations don’t try to make one tool do everything. Automation Studio figures out who qualifies. Journey Builder figures out what happens next. When each tool is doing its job, your whole email marketing system is easier to build, easier to maintain, and easier to explain to everyone on your team.

Beyond the Slide Deck: Designing Digital Marketing Training That Actually Sticks

Kelsey Carr — 2026-08-04T10:01:35+00:00

We’ve all sat through it: click through a slide deck, watch a recorded meeting at 1.5x speed, answer a couple of quiz questions, and forget half of it by lunch. Training happens. Learning doesn’t always.

Whether it’s a full learning and development team or a single HR person wearing ten hats, the goal is the same: turn what subject matter experts know into learning experiences people actually remember, and hopefully even enjoy. That doesn’t require becoming an expert in every facet of digital marketing. It requires partnering with the people who already are, and packaging what they know into something clear, engaging, and approachable for someone learning it for the first time.

Before building a single course, three questions matter more than anything else:

What does the learner need to know?
What do they need to be able to do afterward?
And the one that matters most, why should they care?

Most people aren’t sitting through training to pass a test. They’re trying to solve a problem, do their job better, or avoid a mistake. If the training can’t answer “how will this help me” early, it’s already lost them.

Start With the Learner, Not the Content

It’s easy to fall into the trap of thinking everything is important when working with a subject matter expert (SME) who knows their space inside and out. Usually, it is. But cram it all into one course and learners walk away remembering very little.

Our brains can only hold so much new information at once. So instead of building one giant “Affiliate Marketing 101,” ask what someone actually needs to do after the training. Do they need to recognize different publisher types? Navigate a new network? Understand a policy? Once the outcome is clear, deciding what stays and what can wait gets a lot easier.

Approach training the same way you eat a pizza. Take it one slice at a time rather than trying to eat the whole pie at once.

Make Learning Interactive

Reading slides, watching videos, and listening to a presenter are all forms of passive learning. It has its place, but usually just as a starting point.

Active learning asks something of the learner by giving them prompts to fulfill such as: sort publisher types into categories, work through a real scenario, spot a policy violation, answer a reflection question they’ll actually discuss with their manager, etc. Visuals, light gamification, and interactive exercises all help, but never just to make something “feel fun.” Every exercise should be built to practice a decision the learner will eventually make on the job.

Immediate feedback is where a lot of the real learning happens. Whether someone gets it right or wrong, that moment is a chance to reinforce the concept while it’s still fresh, instead of just clicking “Next” twenty times in a row.

Choose the Right Format

Not every topic needs a full eLearning course, and not every course should look the same. This matters just as much for a lean, one-person operation as it does for a full training team, since the format is what determines how much time and effort a course actually takes to build.

Showing someone how to navigate an affiliate network? A short video or step-by-step visual guide usually does it. Rolling out a new platform feature, policy, or soft skill? A five-minute microlearning is often plenty, and most people can find five minutes far more easily than fifty. Interactive courses are best for practicing decisions or applying a concept to a scenario. Job aids make great references for processes and checklists. And live sessions still matter when the goal is real discussion or coaching.

Stripping out friction matters too. Clear navigation, simple language, intuitive interactions: the less energy a learner spends figuring out the course, the more they have left for the content.

There isn’t one “best” format. There’s only the format that fits the objective.

Learning in Action

Below are two simple interactions built to put “learning by doing” into practice.

Instead of just reading information, learners are making a decision, getting immediate feedback, actively engaging. Small moments like these are what make training memorable, and occasionally, a little fun.

Great Learning Doesn’t End When the Course Does

Learning doesn’t stop at the final slide or the passing quiz score. The training that actually sticks gets reinforced afterward through conversations with managers, job aids, chances to practice, and real-world experience. A course can introduce a concept, but using it is what builds confidence.

That’s also why good training is never really “finished.” Digital marketing moves fast. Platforms update, policies change, best practices shift. Gathering feedback, fielding questions after launch, and updating training regularly keeps it useful instead of stale, whether that’s one person’s job or a whole team’s.

Final Thoughts

Boiled down, the approach comes down to five principles:

Start with the learner
Keep it focused
Choose the format that fits the objective
Give people room to practice
Design for the real world, not just the quiz

Digital marketing moves fast enough that platforms sometimes update before a course is even finished. But great training design was never about capturing every possible detail. It’s about giving people the confidence and skills to keep learning long after the course ends.

At the end of the day, great training isn’t measured by completions or quiz scores. It’s measured by what happens after: when someone makes a better decision, solves a problem faster, or says, “I actually knew what to do because of that training.” That’s when it sticks, whether it comes from a dedicated training team or a single person doing their best to build it alone.

Creative Diversification: Adapting to Meta's Andromeda Update

Hannah Dougherty — 2026-06-22T10:01:35+00:00

Meta fundamentally changed the advertising landscape with the rollout of Andromeda, its AI-driven ad retrieval system. The days of relying primarily on audience targeting, bid caps, and complex campaign structures are over. Now, DTC brands need to pull from a deep well of creative assets with strong messaging and proper audience representation. Media buying has shifted from finding your audience by selecting certain campaign details to supplying Meta with creative inputs that help it find your audience effectively.

So, what does this actually mean for brands trying to scale on Meta?

Creative Production Is Now Non-Negotiable

Creative production needs to be a priority for any brand that wants to scale on Meta. Andromeda needs enough signals via your ads to learn who engages, discover new audience segments, and identify conversion patterns. Think about it this way: if you’re only budgeting for 3 creatives, you’re only giving Meta 3 chances to identify a new customer. The more creative assets you have, the more chances you give your brand to get discovered.

Build for Constant Refresh

Trends move fast, and so should your creative. Brands need to be prepared for consistent refreshes that quickly build upon trends and findings throughout the year. Andromeda rewards fresh signals, and stale creative means stale data.

Build a Testing System

When briefing your team for their next deliverable, guide them with findings: “Customers are responding well to this problem/solution style ad. Let’s think of 3 more, plus video prompts, to show how we offer the solution.”

Consolidate Your Structure

More consolidated structures will be key to getting the most out of your ad dollars. When budgets are spread too thin, Andromeda is missing out on the data points it needs to find audiences a brand didn’t even think of beforehand. The system essentially wants, and eventually rewards, advertisers who give it the most freedom. Consolidated structures also provide better clarity by reducing the number of variables behind why performance is strong.

Trust the Algorithm If the Creative Is Right

If you have the right creative, trust the algorithm to find your audience with broad targeting. Otherwise, advertisers end up competing against themselves by opting into too many narrow segments. A unique factor about Andromeda is its ability to uncover high-intent users who may not fit a brand’s cookie-cutter targeting buckets. As a brand grows, it’s imperative that its media strategy is founded on a consistent ability to find new customers from day one.

Where This Leaves Brands

Meta’s Andromeda is pushing media buyers and marketers alike to come back to the basics: having internal conversations and running tests that ensure messaging and content resonates with users. Ultimately, just as every business is different, so is every ad account.

Andromeda may be named after a galaxy, but it can’t save you from getting lost in space if your creative falls short.

Need help building a creative engine that can keep up with Andromeda? Let’s talk.

From Keywords to Conversations: How AI is Redefining Organic Search

Joshua May — 2026-06-04T10:01:35+00:00

If you’re managing organic search for a brand right now, you’ve probably noticed that the rules have changed. The strategies that drove results two or three years ago are producing diminishing returns, and the platforms your audience uses for discovery have quietly multiplied. In this post, we’ll walk through the changes we’re seeing in organic search, why they matter, and how to build a strategy that can hold up to the everchanging search landscape.

Understanding the New Search Ecosystem

Before getting into tactics, it helps to reframe what SEO (Search Engine Optimization) means today. SEO is no longer just the practice of ranking on Google. It’s the practice of growing a brand’s organic discoverability across the entire digital search ecosystem: traditional search engines, AI assistants, chat-based platforms, social search, marketplaces, feeds, and communities.

That’s a significantly bigger surface area than most brands are currently managing for. And it starts with accepting that Google, while still dominant, is now just one channel among many.

How AI Has Changed the SERP

The most visible shift over the past year or so is how AI has taken over the top of the SERP (Search Engine Results Page). Google’s AI Overviews are now often the first thing a user sees, placed above the traditional links that SEO has always been optimized around.

What’s more, AI answers are increasingly linking to website content as sources. We predict that AI will continue absorbing sponsored sections, local packs, and information cards until it becomes the default SERP experience. Brands that aren’t thinking about how AI retrieves and cites their content are already behind.

A Word on Zero-Click

Zero-click behavior (users getting their question answered directly in search results without visiting a site) has increased alongside the rise of AI answers.

While that concept seems scary on the surface, we’ve found that when AI handles the quick, low-intent queries, the users who do click through tend to be more purposeful and further along in the funnel. The quality of remaining traffic improves, and when those visits are properly nurtured, the revenue impact per visitor increases proportionally. Zero-click is a filter, and it’s one that rewards brands investing in genuinely useful content.

AI Evaluates Websites Like a Human Would

One of the more important developments for how brands should approach content: machine learning now assesses websites the same way that real users do. Search engines and AI systems aren’t just crawling for keywords anymore. They’re also evaluating whether the content truly helps people.

Does the page answer the question? Is it written by someone with real expertise? Does it reflect genuine experience? This is the core of Google’s E-E-A-T framework, which stands for Experience, Expertise, Authoritativeness, and Trustworthiness, and it’s become a central filter for organic performance. Publishing keyword-laced blog posts just to compete for SERP real estate is a failing strategy, and building keyword lists without grounding them in real user intent isn’t enough anymore.

Apps Are Now Search Engines

As AI gets integrated into mobile apps, like Google Maps, TikTok, Pinterest, and beyond, users are increasingly turning to whatever app they already trust to search for what they need. Those apps’ internal search tools have become legitimate search engines in their own right.

A younger consumer looking for a product recommendation isn’t going to Google first. They’re likely searching TikTok, scrolling an Instagram feed, or asking their phone’s AI assistant. A B2B buyer might start on LinkedIn or in a Slack community. This means the keyword has evolved into something broader. It’s now a component of a larger collection of questions, queries, and prompts spread across multiple platforms.

What a Modern Organic Search Strategy Looks Like

Given all of this, the brands that grow through organic search will be those building audience-centered strategies, not search engine-centered ones. Here’s how to put that into practice:

Define Your Search Ecosystem

Not all search platforms serve the same audience, so the first step is identifying which platforms reach the largest share of your specific target audience. A B2B SaaS (Software as a Service) brand and a DTC apparel brand have entirely different search ecosystems. Strategy should follow the audience, not the algorithm.

Research Queries, Not Just Keywords

The old practice of building keyword lists needs to expand into researching the full scope of questions, keywords, and prompts your audience is using. What are they asking? What are they typing into different search bars? What are they prompting AI assistants with? These queries should then be mapped across the funnel so content investment goes where it will have the most impact.

Build Topic Clusters, Not Isolated Posts

Individual posts optimized for single keywords don’t reflect how AI or users process information. Modern content strategy calls for topic clusters, pages that work together to establish depth and authority on a subject. Layer in question-and-answer formats to address specific user queries and invest in original research and expert-led perspectives. Those are the content types that earn citations from AI systems and links from other sites.

Don’t Abandon Technical SEO

Traditional technical SEO is still foundational. AI systems use what’s called RAG (Retrieval-Augmented Generation) which is a process where AI pulls information from search engines to generate factual, real-time answers rather than relying solely on what it already knows. If a site isn’t technically sound and properly indexed, it won’t be retrieved. Brands should also strengthen schema markup and structure content in ways that are easy for AI to process and cite.

Rethink How You Measure Success

Traffic volume and keyword rankings alone don’t tell the full story anymore. A brand can lose clicks and still gain significant influence if AI is regularly citing its content as a source. Measurement frameworks should include content engagement, conversion rates, and the impact of AI mentions and citations on branded search and referral traffic.

The Bottom Line

Keywords still matter, because they reflect how real people express real needs. But they’re no longer the organizing principle of a strong strategy. They’re one input into a broader framework built on audience intent, topical authority, genuine answers, and ongoing discoverability across more platforms than ever before.

The brands that get discovered by AI will be the ones creating content that humans love and that search engines want to surface. Build that, and the visibility will follow.

The search landscape is complex, and keeping up takes the right partner. DMi Partners specializes in modern organic strategies built around audience intent, topical authority, and AI discoverability. Reach out to see what that looks like for your brand.

How to Leverage ShopMy for Smarter Affiliate Attribution & Growth

Ellen Hoffman — 2026-05-28T10:01:35+00:00

If you’re managing creator-forward affiliate programs for multiple brands or products, you already know the challenge: there’s no shortage of data, but turning that data into meaningful growth takes the right tools and the right strategy. ShopMy has become a powerful platform in our toolkit for doing exactly that and, in this post, we’ll walk through how we use it, what to look for, and how we applied these practices to a real DMi campaign.

Understanding the ShopMy Platform

Before diving into strategy, it helps to understand what ShopMy actually gives you access to. ShopMy is essentially a creator-driven affiliate platform that allows brands to connect directly with creators, track performance, and manage campaigns all in one place.

Features vary depending on which package a brand is on, so it’s important to know your capabilities before setting expectations.

Communicating with Creators Inside ShopMy

ShopMy offers several tools that make creator outreach and campaign management much more streamlined than traditional methods. Lookbooks for gifting, creator opportunities, and direct messaging all live within the platform, so you can manage relationships and campaigns without bouncing between tools.

These features create a documented trail of communication and campaign activity that feeds directly into your analytics. What makes ShopMy particularly valuable is that it’s one of the first creator platforms to give brands access to individual creator performance data without requiring a significant upfront investment. Having that granular, creator-level data readily accessible makes it far easier to pull insights and translate them into strategic recommendationsm without needing to commit to a multi-thousand dollar campaign just to learn what’s working.

Making the Most of a ShopMy Looker Dashboard

Beyond ShopMy’s native analytics, our team leverages a proprietary Looker Dashboard that consolidates performance data across our entire brand portfolio, giving us a more streamlined cross-brand view. While building something similar requires internal development resources, the underlying principle is essentially: the more visibility you have across campaigns, the smarter your decisions become.

Here are a few ways we use our Looker dashboard:

Find Pre-Existing Brand Advocates

By filtering the date range to before a brand joined ShopMy Pro, we can identify creators who were already promoting the brand on their own without any outreach or gifting. These are warm, authentic advocates who are often the best candidates for deeper engagement.

Understand Retailer-Specific Behavior

If a brand sells across multiple retailers, the dashboard pulls in performance across all of them. That means you might spot creators driving traffic to a retailer’s site instead of the brand’s DTC site, which is a clear signal to reach out and encourage direct linking.

Track Creator Activity Over Time

Digging into the month-by-month view and expanding to the creator level reveals who’s been consistently active, who’s fallen off, and who might be worth re-engaging through gifting or a new opportunity.

Leverage Cross-Brand Learnings

One of the real advantages of managing multiple brands on ShopMy is being able to cross-reference what’s working. If you’re managing two brands in a similar space, you can look at which creators are performing well for one brand and explore whether they’d be a fit for the other.

Building Relationships That Last

Affiliate programs built on one-off transactions rarely perform as well as those grounded in genuine, ongoing creator relationships. The brands that see the best results from ShopMy are the ones investing in those relationships consistently through regular communication, thoughtful gifting, and personalized outreach.

Getting to know each creator’s strengths, content style, and audience helps you tailor your approach over time. That kind of attention builds trust, and trust leads to more authentic promotion, which ultimately shows up in the numbers.

NAADAM: A Case Study

One of our clients, NAADAM, opted into the ShopMy Pro Package in August 2025. Prior to that, the brand was available for creators to link to on ShopMy, but there wasn’t any outreach, gifting, or direct creator engagement.

Once we onboarded them into the Pro Package, the first step was identifying creators whose audiences closely matched NAADAM’s target customer. Using ShopMy’s analytics, we prioritized partners with strong engagement and a demonstrated ability to drive sales.

From there, we set campaign goals and provided detailed briefs so creators knew exactly what the brand was looking for. ShopMy’s platform also gives brands visibility into any competing or complementary brands a creator is already promoting. This is a very strong filter for identifying creators who are already fans of similar, like-minded brands and are therefore more likely to authentically support yours.

The results after just four months:

300% increase in creators promoting NAADAM via ShopMy
1,723% increase in creator-driven revenue
540% increase in creator-driven traffic
200+ creators gifted
60% promotion rate, meaning 6 in 10 creators who received a gift went on to actively promote the brand through linking

Additionally, 7 of NAADAM’s top 10 revenue-driving creators in that period were net-new partnerships sourced through DMi’s efforts. Relationships that didn’t exist before.

These numbers are a strong reminder of what’s possible when strategy, data, and execution come together. The impact wasn’t just reflected in the numbers. Here’s how NAADAM’s team described the partnership:

“Working with DMi has been a great extension of our influencer strategy team. They’ve helped support and manage our affiliate programs while collaborating closely with us to ensure everything stays aligned with our brand goals and priorities. Especially as a seasonal brand, where so much of our effort is concentrated within key time periods, having a strong partner to help execute alongside our internal strategy has been incredibly valuable.” — Luke Roehm, Social, Influencer, and Creative Operations Assistant, NAADAM

NAADAM offers sustainable, quality cashmere clothing and already has a solid brand foundation and popular product. Layered with consistent performance reviews, proactive creator outreach, and ongoing collaboration between the account manager and influencer teams, we were able to elevate their brand on ShopMy and beyond.

Final Thoughts

ShopMy is a powerful platform that can reliably support your affiliate strategy. Whether you’re just getting started or looking to scale an existing program, the key is to use the ShopMy data to build real relationships with creators, and stay closely aligned between your strategy and execution teams. When all those pieces are in place, the growth potential is substantial, and can last longer than a high-quality cashmere sweater (which is 10 years or more, if you can believe it).