Akaash Joshi shares practical marketing ideas for e-commerce brands, including how to improve landing-page conversion, average order value, and advertising creative. Joshi's posts also cover content marketing and SEO.
Useful for educational e-commerce marketing content on average order value and landing-page conversion.
Best for
DTC brands wanting educational, arithmetic-first posts on AOV and landing-page conversion.
Not for
Campaigns needing verified audience demographics, guaranteed impressions, or standard sponsored-video packages.
Key takeaways
AOV post names product offering, bundling, pre-purchase and post-purchase upsells, price increases, and higher-ticket products.
AIDA post links bounce rate to attention, scroll depth to interest, time on page to desire.
Their AOV example from $20 to $25 is flagged as an arithmetic error.
Check first: Confirm audience demographics, format, pricing, disclosure, and recent AOV or CRO results.
Main ideas
Treat average order value as a growth lever, not an afterthought · Use funnel metrics to make landing-page ideas testable · Make creative strategy central to paid-social growth
Akaash Joshi shares marketing ideas for e-commerce brands, including landing-page conversion, average order value (AOV), paid-social creative strategy, content marketing, and SEO.
Their posts show a practical, metric-oriented style: one maps the AIDA framework to landing-page measures, while another lays out ways to raise AOV.
Buyers evaluating their broader expertise should ask for examples of their other work.
Joshi connects familiar marketing concepts to decisions a brand can measure.
Their AIDA post links attention, interest, desire, and action to bounce rate, scroll depth, time on page, and purchase measures.
Their AOV post pairs possible levers—such as bundles and upsells—with a numerical example.
The example contains a notable error: moving from $20 to $25 AOV at the same order volume raises revenue by 25%, not doubles it.
Readers should recalculate the figures for their own business.
Other posts point to outside material or a podcast rather than presenting the underlying lessons, so the AIDA and AOV posts offer the clearest examples of their approach.
Akaash Joshi’s posts connect marketing ideas to measurable outcomes.
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In e-commerce, they argue that brands should look beyond acquisition costs and conversion rates to average order value; for landing pages, they map a familiar framework to funnel metrics. Other posts point to creative strategy in paid social and structured, data-informed content marketing, though buyers seeking details on their methods should ask for examples.
Treat average order value as a growth lever, not an afterthought
Joshi argues that e-commerce brands can grow revenue by increasing how much each customer spends, rather than focusing only on attracting more orders or improving conversion.
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They list bundles, upsells, product choices, price increases and higher-priced offers for valuable customers as possible levers.
Joshi calculates that 10,000 monthly orders at a $20 average order value yield $200,000 in monthly revenue; at $25, they yield $250,000.
The post calls that a doubling, but the figures show a 25% increase.
The example supports the point that a small AOV change can add substantial revenue, but not the doubling claim.
Use funnel metrics to make landing-page ideas testable
Joshi applies the AIDA framework—attention, interest, desire, action—to landing-page and conversion-rate work, pairing each stage with metrics to inspect.
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Joshi maps attention to bounce rate, interest to scroll depth, desire to time on page, and action to conversion rate, revenue per user and profit per user. The framework helps teams discuss where visitors may be dropping out and what to measure.
Make creative strategy central to paid-social growth
Joshi describes creative strategy as one of the most important elements for a direct-to-consumer brand advertising on social platforms.
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The post promotes a conversation about scaling to more than $50,000 a day; buyers seeking specific tactics should ask what the conversation covers.
Joshi points readers to a podcast with Anze Markovic on scaling and creative strategy. The post signals the subject’s priority, but buyers seeking specific tactics should ask for the conversation’s details.
Organize content around search topics, not isolated posts
In a post summarizing a HubSpot Academy masterclass by Justin Champion, Joshi connects content marketing strategy with SEO structures such as pillar pages, authority content and topic clusters.
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The focus is on organizing related material into a broader strategy. Other short posts point to content engagement and big data; buyers seeking Joshi’s specific methods on those subjects should ask for examples.
The masterclass summary frames pillar pages and topic clusters as parts of an SEO strategy. Joshi’s posts about making a content plan more engaging and using big data link to outside material; buyers seeking their specific methods should ask for examples.
Explains why AOV deserves attention and shows a concrete order-volume calculation.
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Newcomers can see how one metric connects to revenue and get a practical list of levers to test.
Uses a napkin-math example: 10,000 orders a month at a $20 average order value produce $200,000 in monthly revenue and $1.4 million a year.
Raising AOV by $5 to $25 lifts the monthly figure to $250,000 and the annual figure to $3 million.
The post says this doubles revenue, but the listed monthly figures show a 25% increase, and the annual comparison also falls short of a doubling.
It then recommends product offering, bundling, post-purchase upsells, pre-purchase upsells, price increases, and selling higher-ticket products to valuable customers.
For brands planning a campaign
Use the AOV levers as a test menu for a DTC brand, then recalculate the revenue case with the brand’s own order volume and margin. The arithmetic gap is a reason to verify the math, not dismiss the metric.
Shows how to turn a familiar creative framework into a landing-page measurement plan.
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Newcomers can use it to diagnose where a funnel is losing people.
Applies the AIDA principle to CRO and landing pages: attention is bounce rate, interest is scroll depth, desire is time on site or page, and action is conversion rate, revenue per user, or profit per user. Each stage is a metric to inspect, not a slogan.
For brands planning a campaign
A brand can structure a landing-page test around these four metrics and show which stage a change is meant to affect. The framework gives creative and CRO teams a shared metric language.
Shows creative strategy on social platforms as a top priority for DTC brands.
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Newcomers get a quick view of the growth conversation around scaling ad spend.
Announces a podcast with Anze Markovic about scaling to $50k/day or more.
Akaash says creative strategy is one of the most important elements for any DTC brand advertising on any social platform and calls it the one podcast to watch for 2023.
The post names co-hosts Eric Philippou and Nicholas Poole.
Ask for the transcript or recording to assess the specific advice.
For brands planning a campaign
Use this as a signal to audit creative volume and iteration before increasing media spend. Treat the episode as a lead, not verified guidance; review the transcript or recording before acting on it.
Answers a basic content-marketing strategy question and points to a structured SEO model.
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Newcomers can see how Akaash frames educational content as part of search strategy.
Summarizes a HubSpot Academy masterclass by Justin Champion on trailblazing a content marketing strategy. It connects the lesson to an SEO strategy based on pillar pages, authority content, and topic clusters.
For brands planning a campaign
Useful for a brand considering a content-led acquisition channel alongside paid social. The post suggests organizing educational content around clusters rather than publishing isolated posts.
A quick read for someone seeking practical prompts to improve a content plan.
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It shows Akaash sharing outside instructional material alongside original commentary.
Asks whether the reader wants to become a better blogger and links to seven ways to make a content marketing plan more interesting and engaging. The post does not describe the specific tactics; consult the linked list for those.
For brands planning a campaign
Use this as a prompt for a content brainstorming session, not a complete playbook. Read the linked article before acting on it.
Offers a brief statement of a research direction: using large data sets in content marketing.
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Newcomers can see data-driven content among the stated interests.
Says big data is changing content marketing and becomes an incredibly valuable resource when you get a hold of it. The post links out for more; consult the linked material for data sources, methods, and examples.
For brands planning a campaign
Use this as a prompt to look for first-party or industry data for content hooks. The post does not provide a method or proof point.
Akaash Joshi argues that most e-commerce operators fixate on acquisition cost and landing-page conversion while neglecting average order value, and builds the case with simple arithmetic.
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At 10,000 orders a month and a $20 AOV, a brand is at $200,000 a month and about $1.4M a year; every extra dollar of AOV adds roughly $10,000 a month, and moving the same buyers from $20 to $25 roughly doubles annual top-line revenue to about $3M without adding a single order. The levers named are product offering, bundling, post-purchase upsells, pre-purchase upsells, raising prices, and selling higher-ticket products to the most valuable customers.
Napkin math: model revenue from order count and AOV, then name the tactics that move the number.
For brands planning a campaign
A brand can sponsor an AOV teardown using its own order count and AOV, then work through bundle, upsell and pricing options. Measure AOV and top-line revenue at a fixed order count, not conversion rate alone; hold traffic and orders steady and report the AOV lift.
AIDA mapped to landing-page and conversion metrics
Joshi applies the AIDA principle to landing pages and conversion-rate work, assigning a concrete funnel metric to each stage: attention to bounce rate, interest to scroll depth, desire to time on page, and action to conversion rate, revenue per user and profit per user.
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The framework gives each page stage a number to watch instead of relying on a general impression of how it reads.
Stage-by-stage framework applied to a working channel, with one named metric per stage.
For brands planning a campaign
This supports a diagnostic CRO series that pairs each landing-page stage with a metric, showing where visitors drop off. The brand needs to supply real funnel data for bounce rate, scroll depth, time on page and revenue per user.
Creative strategy as the deciding factor in paid social
In a post promoting a podcast with Anze Markovic, Joshi calls creative strategy one of the most important elements for any direct-to-consumer brand advertising on a social platform, in a conversation about scaling past $50,000 a day.
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The format is a recorded conversation with co-hosts, not a written breakdown.
For brands planning a campaign
A brand can sponsor a podcast or recorded conversation on creative strategy for paid social, positioning creative as a constraint on scaling spend. Ask for the specific methods the creator will discuss before treating the conversation as a playbook.
Content marketing strategy through pillar pages and topic clusters
Joshi summarizes a HubSpot Academy masterclass by Justin Champion on building a content marketing strategy, using a search-engine-optimisation approach based on pillar pages, authority content and topic clusters.
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The post points readers to the summary rather than offering a full treatment. Related posts on big data in content marketing and making a content plan more engaging follow the same teaching-by-reference pattern.
For brands planning a campaign
A brand can sponsor an explainer on structuring content around pillar pages and topic clusters, with the creator guiding readers from strategy to page types. Measure organic visibility and topic-cluster coverage over time; ask for the structure to be applied to the brand's own subject area.
Content marketing education through curated link posts
Several posts pair short framing lines with outside articles on content marketing, including making a content plan more interesting and engaging and the effect of big data on content marketing.
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Curated link sharing: a short claim or question, followed by a longer outside source.
Two posts pair a framing line with a link. Ask whether the creator can add their own take on the linked articles.
For brands planning a campaign
This format suits quick distribution of a brand's own long-form piece through the creator's feed, where the post carries the hook and the brand's article carries the depth. It is a weaker fit for a campaign that needs the creator's own detailed position, because the posts reviewed here introduce the subject rather than argue it.
Akaash Joshi’s posts are short, metric-led marketing notes.
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Start with the average-order-value breakdown, then the landing-page AIDA post, followed by the paid-social creative podcast post.
The remaining posts are brief pointers to outside articles on content marketing, engagement and big data.
The through-line is practical arithmetic and funnel measurement for DTC e-commerce, with an emphasis on AOV and conversion over extended treatment of brand or creative strategy.
Taylor Lagace explains DTC performance marketing through detailed numerical systems.
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Their posts walk through a bottom-up paid-media forecast, naming business goals, aMER, ROAS and CPA targets, attribution windows and SKU-level margin outcomes. Joshi uses the same metric-first teaching style to model revenue from order count and average order value and map AIDA to funnel metrics.
Lagace goes deeper into paid-media forecasting, financial planning and attribution mechanics, with stated work for brands such as M&Ms, Purdy & Figg and WildBird. Joshi’s relevant posts are shorter, focusing more on AOV and landing-page metrics than on media budgeting or forecasting.
Tomass Berzins works on the same DTC e-commerce ground, including conversion and the customer experience around an online purchase.
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Their posts discuss why more traffic or a redesign is not always the answer, and how a physical retailer’s advice can translate online. Joshi also treats conversion and landing-page behaviour as measurable topics rather than abstract design questions.
Berzins emphasises operational complexity, teams, delegation, technology decisions and the gap between offline and online retail. Joshi stays closer to revenue arithmetic, AOV levers and funnel metrics, with less focus on organisational challenges.
Adam Kitchen analyses DTC customer economics through order and retention data, including LTV, repeat purchase rates, AOV and the limits of AOV optimisation.
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Their audit example separates first-month spend from later spend and shows how bigger first orders can hide fewer repeat orders. Joshi’s AOV post takes a similarly numerical approach to how order value affects revenue.
Kitchen concentrates on retention, lifetime value and repurchase behaviour over time, often using client audit data, subscriptions, direct mail and text strategy. Joshi’s posts focus more on AOV, funnel metrics, paid-social creative and content-marketing structures.
Treat Akaash Joshi as a topic-fit test, not a verified audience match, for a DTC campaign focused on average order value and landing-page conversion.
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Their posts discuss AOV, CRO, creative strategy, content marketing, and SEO, aligning with the campaign’s subject matter.
The linked LinkedIn account had 4,534 followers as of 9 October 2026, but the posts provide no platform demographic data or audience survey to show whether those followers are DTC operators, founders, marketers, or purchase decision-makers, or to verify their geography, age, gender, employer, occupation, or job seniority.
Ask for recent LinkedIn audience demographics or survey results and recent results on AOV or CRO topics at comparable depth and format.
LinkedIn followers
4534
LinkedIn profile associated with the reviewed posts · 2026-10-09
Akaash Joshi’s posts do not document sponsorship placements, paid partnership packages, sponsored-content rates or an official brand inquiry route.
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They do show a collaborative production habit: one post announces a recorded podcast episode with guest Anze Markovic on scaling DTC creative, credited with co-hosts Eric Philippou and Nicholas Poole.
That shows Joshi appears in and promotes interview-format content, but the post presents it as editorial, not as a purchasable sponsorship slot.
It gives no commercial terms, deliverables or booking process.
Brands interested in a partnership should ask directly about format, pricing and disclosure; the posts establish no standard package.
Akaash Joshi is a good fit for a DTC e-commerce campaign focused on average order value and landing-page conversion, if the brand wants an educational, arithmetic-first treatment rather than a broad-reach sponsored placement.
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One full post on AOV walks from order count and AOV to revenue and names concrete levers: product offering, bundling, pre-purchase and post-purchase upsells, price increases, and selling higher-ticket products to valuable customers.
A second maps AIDA to landing-page metrics: bounce rate for attention, scroll depth for interest, time on page for desire, and conversion rate, revenue per user, and profit per user for action.
That gives the campaign direct subject-matter coverage.
The fit is strongest when the brand provides its own order volume, AOV, margin, and funnel analytics, since their published approach works from those inputs.
The posts do not document a media kit, rate card, or sponsorship package; negotiate the engagement as a confirmed-content collaboration rather than an off-the-shelf sponsorship slot.
Audience demographics are not established, so ask for audience data if a proven DTC buyer audience is essential.
When to choose a specialist
A poor fit is a national consumer campaign that requires a verified audience demographic, guaranteed impressions, and a standard sponsored-video package with usage rights.
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The only dated audience figure in the posts is the LinkedIn account's 4,534 followers, observed on 9 October 2026.
There is no platform demographic data or audience survey showing age, geography, occupation, or purchase authority.
The posts also contain no documented sponsorship terms, rates, deliverables, or inquiry route, and no video transcript or performance summary to support guaranteed reach or engagement.
One post recommends a podcast on creative strategy for scaling DTC ad spend, but it is not a transcript and does not establish a repeatable high-production video offer.
For a campaign that needs audience guarantees and a packaged commercial placement, ask directly for audience data, format, pricing, disclosure terms, and usage rights before proceeding.
A smaller topic-led collaboration remains an option.
A worked campaign example
Worked campaign angle: 'The same orders, more revenue.' Ask Joshi to build a three-part AOV and CRO diagnostic for a DTC brand.
Part 1: an AOV audit using the brand's real order count and AOV.
Use the post's arithmetic: at 10,000 orders a month and a $20 AOV, revenue is $200,000 a month; model what a $1 and $5 AOV lift does at the brand's actual volume, and correct any claim of doubling so the revenue math is accurate.
Part 2: a test menu drawn from the named levers, with the brand choosing two or three: a bundle, a pre-purchase upsell, a post-purchase upsell, or a higher-ticket offer for the most valuable customers.
Part 3: a landing-page diagnostic using the AIDA-to-metric mapping: bounce rate for attention, scroll depth for interest, time on page for desire, and conversion rate, revenue per user, and profit per user for action.
The brand provides its funnel analytics and landing-page test plan; Joshi explains which stage each change is meant to affect.
Measurement plan: hold traffic and order count steady, report AOV lift and top-line revenue at fixed orders, and track the AIDA metrics before and after each change.
Deliver a sponsored explainer plus a written test brief the brand can hand to its CRO and lifecycle teams.
Confirm commercial terms and disclosure before launch; if the brand expects distribution reach, request audience data as well.
Choose Adam Kitchen when the priority is protecting repeat purchasing, not just lifting the first order.
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The posts show they audit cohort data, including 12-month customer value, first-month spend, repeat purchase rate, returning customers per new customer, and returning order AOV, using month-by-month tables.
One audit describes a US outdoor brand whose customer value rose while repurchase rate fell from 10.2% to 8.9% and returning customers per new customer dropped from 0.85 to 0.71; the growth came from first-order AOV optimisation.
A second post reports that, for two brands above $80M in revenue, first-purchase bundling hurt 180- and 365-day lifetime value versus buying items individually — the opposite of what the same post says happens in roughly 95% of cases.
If a brand suspects its AOV gains are masking a shrinking repeat base, or wants its bundle and upsell assumptions tested against its own data rather than accepted as best practice, this is the closer match.
The angle partly reverses a campaign focused on improving AOV first.
The core message: AOV optimisation has a ceiling and eventually can’t make up for fewer repeat orders.
The recommendation is to improve acquisition, first-order value, repeat frequency and repeat spend together, rather than push one lever hard.
A brand that only wants a bundle and upsell menu will get a pushback argument and a data audit instead.
The posts are self-contained audits without the underlying dataset, so the brand would need to provide its own cohort data to run the same analysis on its numbers.
Choose Taylor Lagace when the priority is setting the paid-media spending target and financial plan that AOV work must fit.
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The two posts walk through an 11-step bottom-up forecast for named brands.
It starts with business goals such as exit timeline, target revenue and profitability, then draws inputs from Shopify, Klaviyo and ad platforms: aMER target, first-time and returning AOV, customer file size, repeat rate, gross margin, cost of delivery, fixed costs and churn.
The worked example shows a founder seeking $25M topline at 20% profit against a projected $28M at 12.4% profit.
It then translates the business-level aMER target into channel prospecting targets, accounts for delayed attribution between the 7-day and 28-day windows, and runs every SKU to the same first-purchase contribution margin instead of relying on one blended ROAS.
For a brand that wants to know what a $1 or $5 AOV lift is worth after delivery cost, margin and repeat behaviour are factored in, this provides a bridge from the P&L to the ad account.
The work focuses on forecasting and target-setting, not landing-page or on-page conversion diagnosis.
The posts don’t address bounce rate, scroll depth, time on page or page-level test design.
The approach also assumes clean, correctly pulled historical data across commerce, email and ad platforms.
In a live call, every input is validated; the written version skips that step.
A brand without reliable cohort and margin data would get less usable output.
A brand seeking copy, creative or CRO direction would need a different specialist.
Choose Tomass Berzins when the AOV problem is really about merchandising and store experience.
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One post describes an e-commerce client that is a bike retailer three minutes from their home and draws a direct comparison: a good physical-retail consultant hears what the customer needs, suggests what works together, and sends them out with more than they planned to buy.
Online, that consultant disappears.
The work aims to bring that advice experience online so the purchase feels less like browsing a catalog.
The other post introduces a podcast about growth-side operational problems: more people to manage, more decisions, delegation, CRO and technology decisions, when more traffic or a redesign isn’t the answer, and where AI is useful.
This is a fit when the barrier is how products are presented and recommended, alongside the operational load of growing, rather than an arithmetic gap on the AOV line.
The content offers framing and an experience narrative, not a method.
The posts include no worked AOV calculation, funnel metric mapping or test menu, so a brand expecting a step-by-step diagnostic would need to define one together.
The CRO and technology topics appear as podcast subjects, not detailed post text; the episode itself was not available, so the depth of the CRO positions can’t be judged from this material.
The strength is judgment about the buying experience; the tradeoff is less directly measurable output than the other alternatives.
The profile draws on six LinkedIn posts by Akaash Joshi covering average order value, landing-page conversion, paid-social creative strategy, content marketing, and SEO.
The posts do not show individual dates.
Three posts are short pointers to outside articles and one promotes a podcast; those linked items offer topic signals rather than detail.
No signature book, show, or earlier body of work appears in the posts here, so the public identity picture remains incomplete.
Audience demographics and sponsorship terms are not documented in the posts here.
Where the AOV post's own figures show a 25% increase rather than a doubling, this profile notes the discrepancy so readers can recalculate.
