# Andrew Lolk

Andrew Lolk shares practical advice and examples on ecommerce marketing, including Google Ads, product feeds, Shopping campaigns, and search advertising.

- Profile: https://b2binfluencer.marketing/creators/andrew-lolk/
- LinkedIn: https://www.linkedin.com/in/andrewlolk
- LinkedIn followers: 19,743
- YouTube: https://www.youtube.com/channel/UCz6-WpQWDS2b4UAnGggzJ0w
- Topics: ecommerce, paid-ads, ecommerce-marketing, google-ads
- Based on 10 dated posts, latest 2026-10-08

## Summary

They are most useful for practical ecommerce paid search and product feed advice.

- Best for: B2B ecommerce agencies planning a webinar on Shopping and feed-driven Search.
- Not for: Consumer footwear or apparel brands wanting short-form video awareness campaigns.
- Check first: Confirm recent comparable results, audience demographics, and sponsor terms before contacting.

### Takeaways

- Product-feed data built non-brand Search text ads, reporting 167% more spend, 180% more conversions, 830% ROAS.
- A losing category may need its own target if it can perform at lower ROAS.
- Brand-first product titles are not always right; category terms or benefits may matter more.

## Main ideas

- **Product feeds can turn Google Search into a second Shopping channel**: Lolk argues Search is one of the most underused channels in ecommerce because most teams treat it as manual keyword work: a few campaigns get built, nobody maintains them, Smart Bidding cuts spend when ROAS looks weak, and Search quietly falls below 10% of the budget. The alternative is to run non-brand Search text ads off the same product feed that powers Shopping, so product names, categories, brands, and models fill the ads without hand-built keyword lists. Because the feed keeps the ads relevant, Search behaves like a second Shopping channel at similar ROAS, with its volume arriving on top of what Shopping already delivers rather than replacing it. Their diagnostic is a budget check: if Search is under 30% of total Google Ads spend, money is likely being left on the table.
- **Default feed rules should be conditional, starting with brand-first product titles**: Lolk challenges the near-universal template rule that the brand always belongs first in a product title, noting it appears in every title template they have seen, including their own. The rule is too generic: it fits a shopper searching for a specific brand and model, but not private-label goods, unknown brands, or category-led searches where the shopper is not brand-driven. Their working rules are a short test: are the search terms category-focused, is the brand unknown, and are other benefits more likely to lift click-through rate? A yes to any of these is a reason to move the brand toward the back of the title, not to delete it. A Black Friday collaboration with DataFeedWatch supplies the format for the argument, and the post points to that tool's AI mapping and A/B testing features as one way to run title experiments at scale.
- **Consolidation is the right Smart Bidding default, except when a category keeps losing spend**: Lolk describes themselves as the biggest advocate for consolidating categories into one portfolio and says consolidation remains the right default for most accounts. The exception is a category that loses share of spend month after month inside a shared portfolio and can tolerate a lower ROAS target. A single shared target lets Smart Bidding shift budget toward whichever product line returns more, slowly starving a line with structurally lower but acceptable returns — typically one with higher repeat purchase rates. Giving that category its own tROAS target while leaving the rest consolidated is the fix; they frame it as the exception that proves the rule.
- **Direct-to-consumer math breaks when distribution is treated as a cost instead of a moat**: Lolk examines Nike's aggressive push into selling through its own site and stores, a move intended to arrest declining stock, and concludes that four years on it has not worked. The stated logic was sound — higher margin, control of customer relationships and first-party data, and full control of pricing — and Lolk has seen it succeed for some clients and fail for many. In their account, the failure comes from treating an established retail network as an expense when it functions as a moat: salespeople in local stores do real selling on a brand's behalf, and because several athletic shoe brands are good enough to recommend, that recommendation power is contestable. Neglecting retail forces heavy marketing spend, and the margin gained by going direct is consumed by the cost of discovery. Their conclusion is that companies should focus above all on product quality.

## Work to read

- [Feed-driven Search ads as a second Shopping channel](https://www.linkedin.com/posts/andrewlolk_i-think-search-is-one-of-the-most-underused-activity-7512437471977345024-_o5-)
- [Splitting tROAS by category when one line keeps losing spend](https://www.linkedin.com/posts/andrewlolk_for-six-months-one-product-category-on-a-activity-7513524640045187072-r0i6)
- [Feed myth: brand position in the product title](https://www.linkedin.com/posts/andrewlolk_black-friday-is-closer-than-it-seems-so-activity-7513871916856877057-OVsG)
- [Why the direct-to-consumer push can fail even when the margin math looks right](https://www.linkedin.com/posts/andrewlolk_im-fascinated-by-the-direction-nike-has-activity-7509191055481741312-pFez)

## Brand relationships

- **DataFeedWatch** (disclosed_partnership)
- **Nike** (mention)

## Partnerships

Andrew Lolk has not published a sponsor policy, media kit or partnership inquiry route in the material reviewed; approach them directly. The format with public evidence is vendor co-marketing: in October 2026, they began a collaboration with DataFeedWatch, a feed management platform, to publish a series correcting common product-feed myths ahead of Black Friday. The first instalment presents their rules for constructing titles and points readers to a specific DataFeedWatch feature for running title tests at scale. That pattern—teach a concrete practice, then name the tool that supports it—matches how they write about work generally, using named-account figures (a 167% rise in non-brand Search spend; an 88% spend lift after splitting tROAS targets by category) to carry the argument. Buyers should bring a real product capability they can give Lolk access to demonstrate, not just a logo placement.

## Alternatives

- Jordan Fry: The agency's clients need to know whether the ROAS they are being shown is real before more budget goes in. Fry's two posts take a good-looking number and ask what it actually proves. One covers Google opening Conversion Lift testing to Search and Performance Max without a rep: hold back a group of users who never see the ads, then measure the gap. The point is that a brand search campaign at 10.1x ROAS and $242K of revenue may have collected sales that would have happened anyway. The other walks through a beta Target ROAS calculator that turns a profit margin into a breakeven figure — 667% at a 15% margin — and warns that the margin entered is usually too generous once shipping, returns and fees are counted. For an agency selling measurement as part of the engagement, or a webinar segment on whether brand-search ROAS means anything, Fry covers ground Lolk's posts do not.
- Richard Wyatt: For campaign structure in a feed-driven ecommerce account, particularly one running Shopping alongside Performance Max, Wyatt's longer post sets out a segmentation routine: use a feed platform to label items with fewer than two sales and under 1,000 impressions in the past 30 days; put only those items into their own Shopping campaigns; add best sellers and basket-level converters as further segments; tier the campaigns by priority and ROAS target; and allow items back into Performance Max once they are selling. The rationale is that Performance Max focuses on warm traffic and leaves low-impression items with almost no exposure, so a parallel Shopping campaign picks up revenue rather than competing for it. A second post describes a campaign deep-dive summary that flags products that dropped off, budget pacing, out-of-stock items and channel-mix shifts. For an agency already running Performance Max and trying to recover Shopping volume, this is closer to the working problem than Lolk's Search budget argument.
- Andrew Daniv: The agency is buying an organic search workstream for an ecommerce brand, or the real blocker is the client's decision process rather than the channel plan. Daniv's first post boils an SEO programme down to four monthly deliverables: fix product and category pages built for commercial-intent searches; build internal links with descriptive anchor text; create supporting content that answers buying questions; and acquire links through monthly outreach. It argues against pitches led by long technical audits, dashboards and brand-mention reports with no next action, and includes a worked example of a "standing desk" cluster feeding a commercial page. The second post explains why campaigns stall: pending account and website access, feedback arriving one message at a time, no one holding final decision authority, and every change pushed to the safest option, while the agency gets blamed for a slower timeline. For an agency that loses weeks between recommendation and launch, that second argument is the rarer one.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/