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Q4’e Hazırlık: Adım Adım E-Ticaret Rehberi — Transcript

by Gürkanzone · 8,892 words · 1,352 segments · language en · Watch on YouTube

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0:00Most people preparing for Q4 always
0:01start with the same question. Which
0:03product should I sell during this
0:05period? This is the wrong question to
0:06start with. Because in Q4, finding a
0:08product is usually the easiest part of
0:10the job. The real issue is whether you
0:12have a system to fulfill those orders
0:14profitably once they start coming in,
0:16and setting up that system. That's why
0:18we won't start by looking for products
0:20in this video. First, we will establish
0:21the financial boundaries that will
0:23govern all the decisions we make
0:25throughout Q4. Then, we will place the
0:27product, the market, the offer, the
0:29supply, the store, and the ads within
0:31these boundaries. We aren't starting by
0:33logging into any ad dashboard or store
0:35either. Look. Because dashboards can
0:37change. Button locations change. A
0:39feature used today might appear under a
0:40different name a few months later. But
0:42the math and the system that determine
0:44whether you make money or not do not
0:45change. They haven't changed for years
0:47either. That's why I say that while the
0:48opportunity grows, the cost of making a
0:50mistake during this period also grows.
0:51In a normal period, a bad offer might
0:53lose you a few orders, but in Q4, when
0:55that same bad offer combines with
0:57rising ad costs, it consumes your test
0:58budget in just a few days. In a normal
1:00period, you can manage it if your
1:02supplier is delayed for a day. During a
1:04busy season, that same delay causes
1:05hundreds of orders to pile up, your
1:07support team to get locked, and refunds
1:09to skyrocket. For this, we will have 5
1:11figures in front of us on the first day
1:13. Our usable capital, contribution per
1:15order, break-even customer acquisition
1:17cost, cash conversion cycle, and daily
1:19operational capacity. Now, let's start
1:22with the first figure. Usable capital.
1:24I'm not talking about the total money
1:25you see in your bank account here. I'm
1:27talking about the money you can truly
1:29risk in your Q4 operations. So, we will
1:31consider capital not as a single pile
1:33of money, but as four separate coffers
1:34with different tasks. Now, our first
1:36coffer is the budget we will set aside
1:38for testing. Our second coffer is the
1:40budget for operations. Our third coffer
1:42is for refunds and chargebacks. And the
1:44fourth coffer will be reserved for
1:45scaling the working system. That's why
1:47the Q4 budget is divided before product
1:48research, not after the product is
1:50chosen. Our second figure is the
1:52contribution per order. Contribution is
1:53the money left in our hands to cover ad
1:55costs after a customer places an order.
1:57Meaning, this is not turnover. And it's
1:59definitely not the total amount that
2:00enters the bank account. The point is
2:01the money we can play with. I will
2:03explain this using an example product.
2:05In this video, we will use a modular
2:06desktop organization set from time to
2:08time. Think of it with holders for
2:10different cables. There are under-desk
2:12mounting parts and labels. We will
2:13consider a set like this with small
2:15installation accessories throughout
2:17this video. I'm not saying this is a
2:18successful product or anything. Our
2:20goal is to show you how you should look
2:22at a product through the eyes of a
2:23business owner using this item. Let's
2:25say the customer sees 90 for this
2:27product on the checkout screen. We have
2:29a few costs. The cost of one product
2:31arriving at our warehouse is 320.
2:33Packaging, preparing the order, and
2:34shipping it to the customer is 160.
2:36Let's say the bank commission will be
2:3850. And depending on the structure of
2:39the business, taxes and variable
2:41overheads are 0 per sale. We should
2:42also consider return costs from the
2:44start at a 70%ratio. The total of these
2:46expenses is 790. When we subtract the
2:48790 variable cost from 90 sales, we are
2:51left with a 700 contribution before
2:52advertising. We link this to our 3rd
2:54metric as well. Our break-even customer
2:56acquisition point. If we spend at most
2:58700 TL for one customer, we are at the
3:00break-even point for such an order.
3:01Meaning neither profit nor loss. If we
3:03acquire customers at a lower cost, room
3:05is created for fixed expenses and
3:06profit. Which means we make money. At a
3:08higher cost, the existing structure
3:10starts losing money per order. So, our
3:12break-even ROAS calculation is your 700
3:14net profit. Meaning 2.13 becomes our
3:16break-even point. If our ROAS is above
3:192.13, we are in profit; if it is below,
3:21we are in loss. 4. Our metric is the
3:23cash conversion cycle. The time between
3:24the moment the customer places the
3:26order and the moment that money enters
3:27our business. 5. Our metric is our
3:29daily operational capacity. How many
3:31orders can our supplier prepare per day
3:32? How many orders can our warehouse
3:34process? After how many orders do
3:35tracking numbers start to get delayed?
3:37How many messages can the support team
3:38answer per day? How are reshipments
3:40handled when a defective product
3:42arrives? How quickly can we switch to a
3:44second supplier? These don't really
3:45look like advertising questions, but
3:47these are the answers that determine
3:49the true limit of your ad budget.
3:51Because if you have an operation that
3:53can process 80 orders a day but you get
3:55200 orders, you aren't scaling the
3:57store; you are just scaling the ads.
3:59You have effectively purchased your
4:00future returns and complaints earlier.
4:02You enter an operation you cannot
4:04handle. So, knowing this is important.
4:06And after knowing this, we have
4:07prepared our control board. We know our
4:09available capital. We know our
4:11contribution per order. We know our
4:12break-even customer acquisition cost,
4:14cash conversion cycle, and daily order
4:16limit. Now, as we move within these
4:17boundaries, we can finally place a
4:19product here that deserves to be tested
4:20. We call that product evidence
4:22collection. This is what we are looking
4:24for. So, when researching a product,
4:25our job isn't to browse the internet
4:26and pick an object we happen to like.
4:28It’s not about saying "I can sell
4:29this, it will make money." We collect
4:31evidence from different sources. We
4:32decide which product deserves our test
4:34budget. In the budget portion we have
4:36allocated. And a product looking
4:37interesting is one thing. People paying
4:39money for that product is something
4:41else entirely. A product that has been
4:42watched millions of times on social
4:44media might not sell in the store, or
4:46another product less talked about on
4:47social media can regularly generate
4:49serious order volumes. That is why what
4:51we are looking for here is a product
4:52that truly receives orders, and we look
4:53for three types of evidence in our
4:54research. First is monetary evidence.
4:56Are brands spending advertising money
4:58on this product regularly? Second is
4:59customer language. Why are people
5:01buying the product? Which result do
5:02they like? Why are they returning it?
5:04And the third is behavior. For
5:05behavioral evidence, we check if the
5:07interest came from a single wave of
5:08content or if it stems from a real need
5:10repeated over different periods. Now,
5:11in monetary evidence, we don't look at
5:13just one successful ad, but at ongoing
5:14spending and new content production on
5:16different dates. In customer language,
5:17we are actually looking at people's
5:18reviews. 1, 3, 5 stars—5 stars, okay,
5:21it's liked. 3 stars—there are things
5:23missing; 1 star. It shows that there
5:24might really be an issue in terms of
5:26intensity. In behavioral proof, we
5:27check whether the interest comes from a
5:29single wave of content or a recurring
5:31real need across different periods so
5:32we make the right choice. For example,
5:34asking if people want a tidy desk for a
5:36desktop organizer set is too general.
5:38We want to learn something there. Are
5:39these people bothered because cables
5:41constantly fall behind the desk? Or is
5:43the workspace looking messy during
5:45video calls a problem for these people?
5:47Or are gamers buying this product? Are
5:49people working from home buying it? Or
5:50does this product have a gifting trend?
5:52Now, we will evaluate the list of
5:54different products out of 100 points.
5:56We will make the things I mentioned
5:57above a bit more concrete. This score
5:58is not a scientific market law. It is a
6:00decision system of our own. Our goal is
6:02not to declare a product successful. It
6:04is to prevent us from getting attached
6:05to a weak product just because we like
6:07it. So, we are looking for a testable
6:09product score. We will give 25 points
6:10to demand proof here. We allocate 20
6:12points for marketing, 20 for financial
6:14fit, 20 for operational fit, and 15
6:16points for Q4 fit. In total, our goal
6:18is to create a 100-point set. In the
6:20demand section, we look for different
6:22signals that the product is actively
6:23being sold. Is ad production continuing
6:25? Are new customer reviews coming in?
6:27Is the interest tied to a single day?
6:28If a product has only been viewed a lot
6:30but the proof of purchase is weak, it
6:32cannot get a high score. Or, in the
6:33marketing area, we evaluate the ability
6:35to show the product's benefit in a
6:37short time. Can the before or after be
6:39understood? Can the way it works be
6:40seen? Can we speak to different
6:42customer contexts with that product? Or
6:44can we understand it? A product might
6:45be good, but if explaining its benefit
6:47requires a long conference or
6:49explanation, our job on the advertising
6:51side gets difficult, and in the
6:53financial fit part, we examine the true
6:55cost of the product, possible sales
6:56price, suitability for package sales,
6:58and the break-even customer cost it
7:00leaves us. If one of two products with
7:02the same demand leaves a contribution
7:04margin of 700 TL for advertising while
7:05the other leaves 250, their error
7:07margins are not the same. Or in
7:08operational fit, we look at the
7:10product's size, risk of breakage,
7:11number of variants, let's say quality
7:13control, probability of return, and
7:14secondary supplier options. So, if a
7:16cheap product frequently arrives broken
7:17, it actually turns into an expensive
7:19product. Shipping costs might be low
7:21for these products, but if the customer
7:22constantly chooses the wrong size,
7:24return costs grow. In the Q4 fit, we
7:26evaluate the product's giftability,
7:27packaging reinforcement, delivery
7:29sensitivity, and whether it will
7:31continue to sell after the period ends.
7:33The campaign might be specific to the
7:34period. Look, if possible, the
7:36product's economic life should not be
7:37limited to a few weeks. For example,
7:39let's give the desktop organizer set 17
7:40points from the demand section. Let's
7:42give 18 in the marketing area. Let's
7:44give 16 for financial fit. Let's give
7:4617 for operational fit and 10 points
7:47for Q4 fit. What did we get in total?
7:4978 points. Now, this score does not
7:51mean the product will definitely make
7:53sales. It indicates that the product
7:54can climb to the top of the test list.
7:56So, we are not just picking products.
7:58We determine a test sequence with these
7:59ratings, and some risks are independent
8:01of the score. That is, a product with
8:03uncertain documentation, a counterfeit
8:05brand, uncontrollable quality, an
8:07unmanageable return risk, undeliverable
8:09shipping, or products that might sell
8:11with X, Y, Z health claims we cannot
8:13prove are eliminated, even if they
8:15score high. The second thing as
8:17important as the product is the market.
8:18So, when choosing between Turkey,
8:20Europe, or America, we don't just look
8:22at the size of the market. A large
8:24market is not always the right starting
8:25market. Cheap advertising alone does
8:27not mean it's the right market either.
8:29Look, can we truly understand the
8:31customer's language? Can we technically
8:33offer methods that suit local payment
8:35habits? Can our delivery time compete
8:37with expectations in that market? Can
8:40our order contribution cover the
8:41advertising test? Can we manage returns
8:44and customer support? That is why it's
8:46not about the biggest market. You need
8:47to choose a market where you can fund
8:49your mistakes and read the customer
8:50correctly. Especially if it's your
8:52first Q4, moving the same product to
8:53another country is not just about
8:55translating the store word for word.
8:56Look, the price perception, packaging,
8:58payment, delivery promise, visual
8:59language, and customer objections must
9:01all be reconfigured for that market. We
9:03don't have a randomly selected product
9:04at the end of this section. We have a
9:06test list where the evidence, strengths
9:07, and weaknesses are visible. We know
9:09which product can be tested in which
9:11market and within what risk limits. You
9:13will also learn how to know this in the
9:14video. But the real problem many people
9:16face here is not learning this
9:17information. It is being able to apply
9:19these in the correct order. Today, they
9:21learn product research. Tomorrow, they
9:23research and learn about setting up a
9:24store. The next day, they watch ads.
9:26But the pieces never turn into a single
9:28working system. It goes on in a mess.
9:30That is exactly why we are starting a
9:32camp for Q4. Under normal circumstances
9:34, we had opened a quota for 20 people,
9:36but more than 2,000 people applied. So,
9:39after taking those 20 people, we said
9:41we had no room left and are starting a
9:433-month camp with a workshop everyone
9:45can join. This camp is completely free.
9:48The resources are free, the content is
9:50free, and we will be conducting
9:52everything as a community. All you need
9:54to do to join this camp is to register
9:56for the workshop via the link below. We
9:58will be starting together with a live
9:59broadcast. The workshop will last about
10:012 days, and after that, we will be
10:02embarking on a 3-month journey together
10:04. As I said, in this workshop and
10:05afterwards, nothing will be sold to you
10:07, and nothing will be offered to you.
10:09No offers will be made, and there will
10:10be no product marketing. Our goal is to
10:12make the best of this Q4 with as many
10:14people as possible within these 3
10:16months. As I said, our purpose for
10:18doing this was that we had opened a 20-
10:19person quota. A Q4 camp with one-on-one
10:22consulting. But more than 2,000
10:23applications came in, and after taking
10:2520 people, we unfortunately told the
10:27rest of the hundreds of people "not now
10:29." But this Q4, after all, will only
10:31happen once in 2026. That is why we
10:34will be embarking on a journey with
10:35everyone else as well. Yes, maybe it
10:37won't be one-on-one consulting, but for
10:393 months we will all be evaluating this
10:41period by helping each other out. If
10:43you also want to move forward together
10:45without paying for any training,
10:47without paying any fees, and want to
10:49start your own business during this
10:51period and enter 2027 earning money
10:53from your own store, click the link
10:55below. Sign up. Registration is free,
10:57everything afterwards is free, and the
10:59camp is free. All you need to do is put
11:01in the effort, dedicate time, and be
11:03able to apply what you learn together.
11:06I'm waiting for you at the link below.
11:07Now let's continue with the Q4
11:09preparation side. The most expensive
11:11order in Q4 is not the order we didn't
11:13receive. It is the order you received
11:14but couldn't keep your promise on.
11:16Because that order comes back to you
11:17later as support requests,
11:19cancellations, returns, reshipments,
11:20and payment disputes. That's why we
11:22cannot think of the offer and the
11:23supply as two separate topics. In fact,
11:25our offer is a commercial promise we
11:27make. And supply is our way of keeping
11:28that promise. A good offer provides
11:30clear answers to four questions. What
11:31result will the customer get? When will
11:33the package arrive? When will the order
11:34be delivered? What happens if the
11:36expected result isn't achieved? In the
11:37desktop organization set, we build the
11:39package not based on the number of
11:40items, but based on the job to be
11:41completed. Actually, for cables of
11:43different thicknesses, we can add two
11:45sizes, some surface cleaning wipes,
11:47spare adhesives, cable labels, and a
11:49quick setup card into this package. And
11:51every piece added to the offer has a
11:52cost and an operational burden. The
11:54package grows, the preparation time
11:55increases, and the probability of
11:57sending the wrong part rises. For this
11:59reason, an additional product must
12:00either meaningfully increase the
12:01probability of purchase or reduce a
12:03problem that would arise after the sale
12:04. If it doesn't fulfill these two tasks
12:06, there is no need for it to be in the
12:07package. Look, we won't find the price
12:09only by multiplying the cost by a
12:10certain number. This method might
12:12provide a quick estimate, but it
12:13doesn't determine the real price. The
12:15customer doesn't know how much the
12:16product cost us. Look, they are
12:18comparing the result they will get with
12:19the money they will pay. We are
12:21actually looking at three separate
12:22accounts for the price. What is the
12:23value perceived by the customer? What
12:25are the alternatives in the market? And
12:27what is the contribution the order
12:28leaves for the business? So, by looking
12:30only at the competitor, we might copy
12:32their bad math. By looking only at the
12:34cost, we might sell a product for
12:35unnecessarily cheap that the customer
12:36is willing to pay more for. Or, if we
12:38rely only on the value narrative, we
12:40might choose a price that the market
12:41does not accept. That's why these need
12:43to be in coordination. They need to
12:44progress together. In our 490 example,
12:46remember our pre-ad contribution was
12:48700, and when we lower the price, the
12:50conversion might increase, for example.
12:52But the remaining space for advertising
12:53also gets smaller. When we raise the
12:55price, our order volume may drop, our
12:57conversion may drop, but our
12:58contribution per order grows. So, let's
13:00assume the first price brings 20 orders
13:02a day and we have a net profit of 150
13:03per order after advertising. After
13:05deducting the ad cost. So what is its
13:07daily contribution to us? Our total net
13:09profit is 20 x 150, which is 3,000. Now
13:11, our second price brings 16 orders a
13:12day, but if it leaves 240 per order,
13:14the expensive price. Our daily
13:15contribution becomes 16 x 240, which is
13:183,840. So, even though the price is
13:20higher and orders and conversion rates
13:21have dropped, it still yields more
13:22profit for the business. That is why we
13:24do not evaluate price tests solely by
13:25the conversion rate. We need to examine
13:27order quantity, customer acquisition
13:29cost, and total contribution together.
13:30We also don't force the customer into
13:32nonsensical quantities just to increase
13:33the average cart value. Look, this is
13:35one of the biggest mistakes I see. A
13:36starter cost can be prepared for a
13:38single desk, a home package for a desk
13:40and TV unit, and an expansive package
13:41for home and office. The package name
13:43explains why the customer should buy a
13:44higher quantity. It is not like "buy 2,
13:46get 3, buy 7" or similar approaches.
13:48The Q4 package offer also has a real
13:49time limit. The end date of the
13:51campaign is already clear. Between
13:52current stock levels and the final
13:54delivery date, there is already enough
13:55urgency. You don't need those repeating
13:57countdown timers or fake stock alerts.
13:59If we promise delivery by a certain
14:00date, our operations must keep that
14:02promise. Selling as if the product will
14:04arrive on time when it won't brings
14:05revenue in the short term. But it
14:06creates cancellations and a support
14:08burden just a few days later. Once our
14:10offer content and price are set, we
14:11know exactly what we need to procure.
14:13We will procure not just the main
14:15product, but also the parts within the
14:16package, the packaging method, and the
14:18delivery promise. We won't make
14:19procurement decisions based on the
14:20question of where to find the cheapest
14:22product. The right question is: How can
14:23I ship this product with a level of
14:25risk appropriate for my current stage?
14:26So, you don't have to stock up with
14:28high quantities from day one. Buying
14:29large amounts of stock without seeing
14:31the sales, return reasons, and quality
14:33issues creates unnecessary risk. On the
14:35other hand, looking for solutions as
14:36orders come in without any preparation
14:38unfortunately doesn't match the speed
14:39of Q4. Our first stage is the sample.
14:41Here, we don't just look at whether the
14:42product looks good. Look, we examine
14:44the package, materials, dimensions,
14:46ease of use, and potential damage
14:48during shipping, and we set up the
14:49product just as the customer would. If
14:51possible, we even try it ourselves for
14:53a few days. The second stage is what we
14:55call procurement as orders arrive. So,
14:56in the initial tests, you can ship the
14:58product individually or in low
14:59quantities. Your unit cost will be
15:01higher. Yes. Your delivery will be
15:03slower. So, it is not an ideal
15:04operation. But in return, you haven't
15:06tied up a large amount of capital in
15:07the product before sales are validated.
15:08The most valuable thing we buy at this
15:09stage is not stock. Look, it is
15:11information. Is the customer receiving
15:13the product? Is the package arriving
15:14complete? What are the most frequent
15:16complaints? What are the reasons for
15:17returns? Is the supplier preparing the
15:19order on time and as promised? If the
15:21product continues to sell across
15:22different days and different creatives,
15:24we can move to a small batch, a small
15:25inventory step. There is no
15:27one-size-fits-all quantity here. Look,
15:28for some products 20 units might make
15:29sense, while for others 50 might be
15:31logical. So, we make the decision based
15:32on your daily sales speed, lead time,
15:33and the cash you can set aside for risk
15:35. When choosing your supplier, we won't
15:36just look at the unit price. Look,
15:38first we send the exact same product
15:39description to all candidates. Saying,
15:41"I want this product." Our materials,
15:43measurements, package contents, product
15:44weight, packaging, and the quality
15:46level you accept must be clearly
15:47written, or you send the exact product.
15:49We ask our manufacturer about the lead
15:51time, daily order capacity, when the
15:53tracking number is generated, what
15:54happens with defective products, and if
15:56capacity changes during busy periods.
15:58And the real supply cost does not
15:59consist only of the product price. Our
16:01shipping, packaging delays, error
16:03margins, reshipment, and support burden
16:05must also be included in this cost. You
16:08can also find the reorder time for a
16:09working product with a simple
16:10calculation. Look, our reorder point is
16:12the average daily sales multiplied by
16:14the sum of the lead time and safety
16:16time. Let’s say, for example, the
16:18product sells an average of 18 units
16:19per day. And let it take 12 days for a
16:21new batch to reach us from the supplier
16:23. For possible delays, add a safety
16:25margin of, say, 5 days. That makes 17
16:27days. Now you have 18 days of sales.
16:29You have a 17-day lead time to restock.
16:31Then you need 306 units. That you need
16:34to pull in. We don’t use this
16:35calculation before the product is
16:37verified and buy 306 units on day one.
16:39Look, our formula is to prevent
16:40stockouts for a working product. We
16:42protect our capital during the testing
16:44phase. We move to inventory management
16:46only when demand repeats. A single
16:47sales forecast for Q4 is not enough
16:49either. You need to prepare separate
16:50scenarios for normal sales, strong
16:52sales, and supply delays. In how many
16:53days does the stock run out at a normal
16:55pace? If our sales increase by 1.5 x,
16:56how many days will it last? If the
16:58supply is delayed, on which day do we
16:59become unable to fulfill orders? If
17:01there are no answers to these three
17:02questions, it means we are not ready to
17:04aggressively increase the ad budget. So
17:06far, we have established our product,
17:07our offer, and our supply models in our
17:09heads. But the customer knows nothing
17:11about any of this. Your customer sees
17:13your ad. They come to your store and
17:15decide within a few minutes whether to
17:17trust us or not. When the customer
17:19clicks on the ad, the store's first
17:20task is not to create a new promise. It
17:22is to show that the promise in the ad
17:24continues on the right page. So there
17:26needs to be consistency between them.
17:28Whatever problem the ad opened up, the
17:29first section of the page should answer
17:31that problem. Whatever use case the ad
17:33showed, the first visual on your site
17:35should continue that same use case. If
17:37a specific package or price was offered
17:38in the ad, they shouldn't encounter a
17:40different offer on the page. The
17:41customer goes through four decisions on
17:43the page. Look, first they think, "Is
17:45this product for me?" Then they try to
17:46understand how it works. After that,
17:48they decide whether to trust the
17:49product and the store. In the final
17:51stage, they evaluate the price,
17:52delivery, and risk, and the first
17:54section captures the right customers.
17:55The environment where the product is
17:57used, the main result, the package, and
17:58the purchase option should be clearly
17:59visible. The headline doesn't even have
18:01to be overly creative. Look, it needs
18:02to be understandable here. Instead of a
18:04"rediscover your life" sentence that
18:06could be used for every product, you
18:07need to explain the change the product
18:09provides to the other party clearly.
18:11The second section is to show how the
18:12product works, the mechanism. If we
18:14only present a result image, the
18:15customer may not believe that the
18:16result was created by the actual
18:18product. Most of the time, they don't
18:19believe it. Because there are hundreds
18:21of places making promises. We show in a
18:22simple way how the holder is attached
18:24to the surface, how the cable is placed
18:25, and how it is removed when necessary.
18:27We need to explain the mechanism. On
18:29the trust side, section 3. Trust does
18:31not arise solely from payment logos.
18:32Look, claims must be consistent and
18:34provable. Real usage footage, relevant
18:36customer experience, and mechanism
18:38demonstrations can be used here. To
18:40show that you stand behind what you
18:41promised the other party. And the 4th.
18:43section is purchase terms. Package
18:45content, selected options, your
18:47shipping costs, preparation time, and
18:48return policies must be very clear. Do
18:50not hide delivery information in the
18:52back pages of the site, especially. If
18:53the product is being bought as a gift,
18:55the delivery date is as important as
18:56the product's features. In Q4, the
18:57store's second test begins when the
18:59customer adds a product to the cart.
19:01Because adding to cart does not mean
19:02making a purchase. Here, the customer
19:04encounters shipping, delivery, form
19:06length, payment security, etc., and the
19:07payment step should be as predictable
19:09as possible for the customer. Meaning,
19:11we will not ask for information that we
19:12do not need to deliver the order and
19:14complete the payment. Every new field
19:15adds a new point where the customer
19:17might make a mistake or give up.
19:19Because requesting every single piece
19:20of information. Choosing a payment
19:22provider based solely on commission is
19:23not correct either. If a system
19:25offering lower commissions rejects a
19:27real customer's payment, it costs more
19:29in total. We really need to work with
19:31compatible infrastructures. Does it
19:33accept the cards and payment methods in
19:34the target market? What is the schedule
19:36for transferring funds? How does it
19:38handle returns and payment disputes?
19:39What security checks are used for
19:41suspicious transactions? Does it
19:42provide support during peak periods? We
19:44evaluate these together. And when the
19:46payment is completed, look, the correct
19:47package must be deducted from inventory
19:49. It must be transferred to the supply
19:50side with the correct product code, and
19:51a confirmation message must reach the
19:53customer. We have suffered a lot from
19:54this, because in parts involving
19:55sending the wrong product, if the
19:57customer buys a large package and a
19:58starter package goes to the supplier,
19:59everything looks successful on the ad
20:01side. ROAS increases or whatever, but
20:02the problem appears a few days later
20:04when the package is opened. In the
20:06measurement system, product page views,
20:07cart additions, payment initiation, and
20:09purchases are tracked as separate
20:11events. This chain shows not only the
20:13sales count but also, look, where the
20:15system is breaking. If measurement is
20:16done from both the browser and the
20:18server, the same order should not be
20:20counted twice. When the same purchase
20:22is sent via two channels, it must be
20:24matched with a common event or order ID
20:25. The amount and currency must also be
20:28sent correctly. This needs to match
20:30with both automatic and manual setups.
20:32If a 90 TL order goes through as 1490
20:34dollars, the entire report is ruined.
20:36For this reason, place a real test
20:38order before running ads. Is the
20:39product entering the cart with the
20:40correct price? Is the package option
20:42correct? Is the payment being completed
20:43? Does the order drop only once? Are
20:45there duplicates? Is the purchase being
20:47measured with the correct amounts? Does
20:48the inventory decrease, does the
20:49correct product go to the supplier, and
20:50does the confirmation message reach the
20:51customer? We do not manage cash needs
20:53by looking at the surface, either. Look
20:54, we multiply the number of daily
20:55orders by the amount we spend out of
20:57pocket per order before the transfer
20:58and the time it takes for the money to
21:00become available. Let's say you receive
21:0230 orders a day. We need to pre-finance
21:04an average of 820 per order for ads,
21:06products, and shipping. If the money
21:08becomes available after 4 days, then at
21:1130 x 820, we need 24,600 to finance per
21:14day. That's nearly 100,000 for 4 days.
21:17This figure is not a loss. Look, this
21:18is the working capital needed to
21:20finance orders until the money hits the
21:21account. We also calculate the refund
21:23reserve based on real data. If the
21:25probability of a refund is 10%and the
21:27average amount we earn per return is
21:28700, then the expected loss per order
21:30is 70. 10%of 700 makes it 70. This is
21:33how we derive the 70 we put into the
21:34cost table in the first section. At the
21:36end of this section, we have
21:37established a single order system from
21:39advertisement to delivery and money
21:40transfer. Now we can move on to
21:41preparing the creative stock that will
21:43bring customers to this system. If you
21:44have understood the logic, the products
21:46in the warehouse are not the only stock
21:47that runs out in Q4. Your capacity to
21:49grab the customer's attention also runs
21:51out. When an ad starts working, many
21:53businesses put the entire budget behind
21:55it. They use the same image and message
21:56for weeks. When results drop, they try
21:58to urgently produce new content.
22:00Creative production is not a planned
22:02system. It turns into an intervention
22:03tool used when a fire breaks out. We do
22:05the opposite. Just as we established a
22:07stock and reorder plan for physical
22:09products, we will create a creative
22:10stock for advertising. We need to
22:12create it. We will know and plan which
22:14message, image, and proof will appear
22:16in what order before the working ad
22:18gets tired. That is why we will
22:20determine what we want to prove before
22:21even turning on the camera. For this
22:23desktop organizer set, the customer
22:24won't wake up in the morning and think,
22:26"I should buy a cable holder today."
22:28They don't think that. They feel the
22:29need when the charging cable falls
22:31behind the desk again, when they notice
22:33the desk looks cluttered during a video
22:35call, or when they deal with those same
22:36cables while cleaning. We will make
22:38them feel these moments. Then we will
22:40identify the doubt that prevents the
22:41customer from purchasing. Will the
22:42adhesive part come off? Does a thick
22:44cable fit? Will it leave a mark on the
22:45desk? Is it a hassle to install? Does
22:47it look as neat as it does on the
22:48internet? These sentences are not
22:50problems. Look, these are the
22:51descriptions of the proof we need to
22:52show. If the customer thinks the
22:54adhesive won't hold, just writing "
22:56strong adhesive" is not enough. We will
22:58show how the surface is prepared, how
23:00the piece is fixed, how it moves during
23:02use, and how it doesn't get in the way.
23:04If they think a thick cable won't fit,
23:06we will compare different sizes in the
23:08same shot. If they think installation
23:10is difficult, we will show the process
23:12uninterrupted to the other side. As the
23:14distance between the claim and the
23:15proof shortens, the persuasion power of
23:17the ad increases. One needs to
23:18distinguish four concepts here. The
23:20angle is the customer's reason for
23:21purchasing the product. The hook is the
23:23first image or sentence that grabs
23:24their attention before they skip the ad
23:26, making them believe the promise we
23:27are providing proof for. What we call
23:29format is the way the message is
23:31presented, such as a user video,
23:32demonstration, comparison, or static
23:34image. So, for our example, the first
23:36angle could be daily annoyance. For
23:38instance, a hand searches for a
23:39charging cable that fell behind the
23:40desk. Then they see that the cable
23:41falls to the same place every time it
23:43is left alone. The product steps in,
23:44and the cable stays at the edge of the
23:45desk. The main promise of this creative
23:47is not a pretty desk. It is reducing a
23:49small, daily recurring chore. The
23:50second angle is visual transformation.
23:52In the first frame, the desk with messy
23:53cables and adapters is shown, followed
23:55by the organized version of the same
23:56desk. What we call proof is the
23:57difference between the before and after
23:59. Let's call the third angle work
24:00efficiency. The customer opens their
24:02computer. They easily grab their
24:03headphones and charging cable. When
24:04finished, they put them back in their
24:05place. The product is positioned as a
24:07small system that doesn't disrupt the
24:08workflow. The fourth angle is the Q4
24:10gift. However, just putting a ribbon on
24:12the product and writing "perfect gift"
24:13isn't enough. We need to show who it's
24:15gifted to and why it would be used. It
24:16can be described as a useful package
24:18for someone working from home, gaming,
24:20or setting up a new workspace. Our four
24:22angles. Let's assume we have 3
24:24different openings for each angle and
24:25two types of proof for each opening.
24:27And 4 x 3 = 12, 12 x 2 = 24
24:29combinations. This doesn't mean we will
24:32publish 24 ads on the first day. Look,
24:34it shows that we have a production map
24:36consisting of 24 possibilities. We are
24:37creating a roadmap for ourselves here.
24:39In the first small group, we keep the
24:41format and offer the same and compare
24:42the angles. When we find the working
24:44angle, we keep it fixed and change its
24:46openings. Then, we test it through
24:47proofs like demonstration, comparison,
24:49or customer experience using the same
24:51angle and opening. This sequence
24:53teaches us not only which ad works, but
24:55why it works. If we change the angle,
24:57the actor, the offer, and the page all
24:58at once, sales might come, but we can't
25:00understand which variable produced the
25:02result. On the production side, we
25:03don't have to do new shoots every week.
25:05With the right plan, we can create a
25:06library of footage in a single shoot
25:08that can be used for a long time and
25:09put it in a drive. You take a wide shot
25:11of the messy desk once. We already film
25:13the falling cable, the temporary
25:15solution, the unboxing, the surface
25:17cleaning, the installation of the
25:19holder, different cable sizes, daily
25:21use, and the organized desk separately;
25:23if every image is clean and clear
25:25enough to be recombined in different
25:27ads, we can constantly recycle them
25:29from the Drive folder. A problem ad can
25:31start with the falling cable, a
25:32conversion ad with a comparison of the
25:34messy and organized desk, a setup ad
25:36with surface cleaning, and a gift ad
25:38with package contents. A single shoot
25:39is used for different hypotheses, and
25:41while production costs drop, the speed
25:43of testing increases. There are
25:44different tasks for Q4 creative stocks.
25:46Look, core benefit creatives
25:47independent of the period show us the
25:49normal demand for the product. Q4
25:50creatives explain the package and real
25:52campaign conditions. Objection
25:53creatives address delivery,
25:55installation, and trust. And final
25:56period creatives explain the actual
25:58delivery deadline and remaining time to
25:59us. When performance drops, we don't
26:01throw everything away. If the purchase
26:03justification is working, the opening
26:04might be fatigued. So in this case, you
26:06keep the angle and we change the
26:08initial image. If the opening grabs
26:09attention, the proof might be weak. We
26:11refresh the application part. If the ad
26:13brings clicks but no sales, the problem
26:14might be a transition issue between the
26:16ad and the page rather than the
26:17creative. We no longer have just a few
26:19random videos. Look, we have a creative
26:21stock system where we know which
26:22purchase drivers, which angles, and
26:24which doubts to test. Now, in ad
26:25results, we see many numbers like
26:27impressions, clicks, page views, add to
26:30carts, checkout initiation, purchases,
26:32customer acquisition cost, and ROAS.
26:34All the numbers may be correct. If we
26:36interpret them in the wrong order, we
26:37make the wrong decisions again. A high
26:39click-through rate might be mistaken
26:40for a good ad. However, if people are
26:42clicking but not buying, we might just
26:44be attracting cheap traffic, or
26:45bringing the wrong people to the wrong
26:47offer. You might think high revenue is
26:48a success, but if sales are being
26:50double-counted due to a measurement
26:51error, you might be inflating a profit
26:53that doesn't exist. That’s why ad
26:55data doesn't tell us exactly what to do
26:57. It shows us what is happening in
26:58which part of the system. Our business
27:00math makes the decision. We reduce the
27:02variables before starting the test. If
27:04we use 3 prices, 2 pages, and 20
27:06creatives across 5 markets all at once,
27:08we won't understand the results even if
27:10we get them. We shouldn't move randomly
27:12. We will have one main market. We will
27:14have a core offer. We will have a
27:15verified page and choose small creative
27:17groups based on specific hypotheses.
27:19Instead of thinking about how much to
27:20spend daily, we will scale the test
27:22budget based on how many break-even
27:23customer acquisition costs we can risk.
27:25So, if the total test budget is 21,000
27:27and the break-even acquisition cost is
27:29700, we have 30 units of testing room,
27:31calculated as 21,000/700. For that test
27:33process. We need to read the results
27:35like a funnel moving from top to bottom
27:37. Impressions, link clicks, actual page
27:39views, add to carts, checkout
27:41initiations, purchases. Meaning, we
27:42will answer different questions at each
27:44step. Impressions show the ad was
27:46distributed; clicks mean the message
27:47generated interest; page views show the
27:49person reached the store; add to carts
27:51are the first strong intent signal for
27:53the offer; and checkout/purchase shows
27:54if the store finishes the job. So, we
27:56started with our promise here; our
27:58system and ad work, having spent 14,000
28:00and received 350,000 impressions.
28:02Let’s say 3,500 link clicks arrived.
28:04About 3,000 people reached the product
28:06page. 252 of them added to the cart.
28:08126 started the checkout step. There
28:10are around 40 purchases. To find the
28:12cost per 1,000 impressions, we divide
28:1414,000 by 350,000. We multiply by 1,000
28:16. The result is 40. The link
28:17click-through rate is 3,500/350,000 x
28:20100, which is 1%. Our cost per click is
28:2314,000 for 3,500 clicks. Since 3,000 of
28:25the clicks reached the page, our
28:27click-to-page transition rate is 3,000/
28:293,500, or 90%. Our add-to-cart rate is
28:31252/3,000, which is 8%. For the
28:34transition from cart to checkout, if we
28:36say 120 out of 250, it's about 50%.
28:38Since 42 of the 126 people who started
28:40the checkout purchased, our completion
28:42rate from cart to purchase is 33%. Our
28:44total page conversion rate ends up
28:47being 1.33%. So, with 14,000 in
28:49spending and 42 purchases, our customer
28:51acquisition cost is 333. If each order
28:54is 1,400, the measured revenue is 42 x
28:571,400, which is 62,000; dividing that
28:59by 14,000 gives us a ROAS of 4.47. But
29:02the real contribution hasn't been
29:03calculated yet. Our pre-ad contribution
29:05per order was 700. 42 x 700 equals
29:0829,400. And from this, we will subtract
29:10the ad spend. Then our remaining
29:12contribution, our usable profit, is
29:1415,400. If the ad isn't being shown
29:16enough, distribution, target audience
29:18limits, payment, or technical setup are
29:20checked. If impressions are coming but
29:21people leave at the start, the landing
29:23page view and the communicated message
29:24might be weak. If the ad is being
29:26watched but link clicks aren't coming,
29:27the content may have generated interest
29:29. But a commercial bridge to the
29:30product wasn't built, or a good enough
29:32motivation to click might not have been
29:33provided. You've prepared an
29:35entertaining video. But you haven't
29:36told the viewer why they should visit
29:38the store. If there are clicks but page
29:40views are low, before blaming the
29:42creative, check site speed, links, and
29:45tracking. To see if there's a technical
29:47issue. If the page loads but there's no
29:49add-to-cart, there may be a disconnect
29:51between the ad and the store, a weak
29:53offer, or trust issues. If they add to
29:56cart but checkout initiation is low,
29:58check shipping costs, delivery times,
30:00packaging options, or unexpected totals
30:03. If they start checkout but don't
30:05complete it, check payment methods,
30:07form errors, verification, or technical
30:09bugs. If sales are coming in but the
30:10customer acquisition cost is above your
30:12break-even point, you might be making
30:14sales. But the unit economics aren't
30:15strong enough to sustain the ad. Price,
30:17bundles, average order value, and
30:19variable costs must be re-evaluated. We
30:22can make three decisions for an ad. We
30:24can shut it down, fix it, or scale it.
30:26The decision to shut down isn't made
30:28just because there are no sales. If the
30:29creative's hypothesis doesn't resonate
30:31in the funnel and lags behind similar
30:33tests, we can stop it. The decision to
30:35fix is made when the ad generates
30:37interest and clicks, but sales are lost
30:39in the next step. Instead of throwing
30:41away a working creative, you need to
30:42fix the landing experience, the offer,
30:44or the checkout process. The decision
30:46to scale doesn't rely on a single day's
30:48sales. See, the customer cost must stay
30:50within business limits, results must be
30:51repeatable, and operations must handle
30:53the new volume. However, we can also
30:55look at the current position
30:56mathematically. If a creative spent
30:582,800 and the break-even customer cost
31:00is 700, it needs at least 4 sales to
31:02break even by then. 2800/700 equals 4.
31:06If it only generated 2 sales, your
31:08current customer acquisition cost is
31:102800 divided by 2, which is 1400. This
31:11isn't an automatic shut-down order, see
31:13. But it does show the ad's economic
31:15position as a discussion point. Then,
31:17you need to examine the cart, checkout,
31:19delayed sales, and compare it with
31:20other creatives. And scaling isn't just
31:22about increasing the budget. You need
31:24to grow the media budget, creative
31:26variety, order economics, and
31:27operational capacity together. We can
31:29open more space for a working ad. We
31:31can produce new angles and proof points
31:33from the same sales premise. By
31:34improving bundles and average order
31:36value, we can get a stronger
31:37contribution from the same customer. We
31:39can scale inventory, support, and cash
31:41capacity based on order velocity. If we
31:43only increase the ad budget out of
31:44these four areas, we put the rest of
31:46the business under pressure. Before
31:47aggressive growth, the ad must be
31:49profitable, results shouldn't depend on
31:51one day, payment and supply must handle
31:53volume, and the cash gap must be funded
31:55. In other words, a store dependent on
31:57a single creative is fragile. If
31:59possible, you need to develop multiple
32:00creatives that generate sales from
32:02different angles. When one ad fatigues,
32:03the entire store's sales shouldn't stop
32:05. In retargeting, we don't just show
32:07the same ad to everyone who visited the
32:09site. See, the customer's last signal
32:11provides a clue as to which problem
32:13hasn't been solved yet. But retargeting
32:15doesn't always mean a separate, large
32:17budget for every store. If traffic
32:18volume is low, segments can stay too
32:20small, and the ad might be shown to the
32:22same people too often. In such a case,
32:24it is healthier to benefit from the
32:25reach of the main campaign rather than
32:27fragmenting the system unnecessarily.
32:29We use retargeting not because it’s a
32:31habit, but when we can respond to the
32:32signal a customer leaves with a
32:34different message. Creating segments on
32:36its own is not a strategy. Because you
32:38need to define a truly different and
32:40meaningful task for each segment for it
32:42to be a strategy. Now we can place the
32:44entire system into a Q4 calendar. The
32:46weeks here are not fixed campaign dates
32:48, but a countdown to the period when
32:49sales will peak. No matter when you
32:51watch this video, you can set up the
32:53same structure based on your own peak
32:54week. Now, 8 to 6 weeks before the peak
32:56, we must have cleared the
32:58infrastructure and uncertainties. We
32:59need to know our available capital,
33:01breakeven customer cost, and cash
33:03conversion cycle very well. We must
33:05have scored our product lists. Samples
33:06will be taken, and quality control will
33:08be performed. At least one alternative
33:09supplier will be researched. During
33:11this period, the payment flow is also
33:12tested with real orders. It is verified
33:13that the purchase event is measured
33:14with the correct amount and currency.
33:16Scenarios like cancellations, returns,
33:17and failed payments are tested. It is
33:19clear on paper. The base product page
33:21is prepared. It is checked on mobile
33:22devices. Then, 6 to 4 weeks before the
33:24peak, the offer and creative must be
33:26validated. First, we will test a core
33:27offer independent of the period. This
33:29way, we understand what we can actually
33:31improve when the Q4 discount or package
33:33goes live later. Which angle is the
33:34customer responding to? Is it daily
33:36relief, visual transformation, workflow
33:38, or gift context—which opening
33:40brings clicks? Which proof increases
33:42cart additions? We are seeking the
33:44answers to these questions. Look, in
33:45price testing, we don't just look at
33:47the conversion rate. We will evaluate
33:49our order volume, customer costs, and
33:51total contribution together. If a lower
33:53price brings more orders but leaves
33:55less money for the business, we won't
33:56blindly choose it. At the end of this
33:58period, we want to see not that we can
34:00sell the product, but with which offer
34:02and message we can sell it economically
34:04—that is, profitably. 4 to 2 weeks
34:06before the peak, operations are
34:08prepared. We will outline scenarios for
34:10normal daily sales, strong sales, and
34:12delays. You must know your days of
34:14inventory and reorder point very well.
34:16We must verify the supply status of
34:17every part within a package. The whole
34:19order shouldn't be held up because a
34:21small gift is out of stock while the
34:22main product is available. So, you will
34:23plan how you will proceed with partial
34:25products. Canned responses for customer
34:27support regarding deliveries, returns,
34:29and so on will be created. The goal
34:31here is not to send people the same
34:32message like a robot. It is to provide
34:34accurate information quickly and
34:35consistently during the rush. The
34:37payment transfer calendar and the days
34:39for ad and supplier payments are placed
34:40side-by-side. The cash gap that will
34:42occur when sales double is foreseen in
34:44advance. We don't want to turn off
34:45profitable ads just because there is no
34:47cash left to pay the supplier. We will
34:49prepare new angles and proofs for the
34:50active creatives. These are the visuals
34:52for the Q4 offer, the actual campaign
34:54dates, and delivery messages. They are
34:56sent to production. This way, we won't
34:57enter the campaign week with a single
34:59ad. And we won't be trying to discover
35:01the system from scratch in the final
35:02two weeks. We will scale the previously
35:03validated products, offers, and
35:05creatives with messaging appropriate
35:06for the period. Scaling, or new tests,
35:08can continue during that time, but we
35:10absolutely do not tie the main budget
35:12to unproven ideas. During this period,
35:14stock and delivery information on the
35:15store must be updated regularly. The
35:17price used in the ad must remain the
35:19same as the price on the product page.
35:20The campaign code must be functional.
35:22Package options must match the stock,
35:23and mobile payment and order
35:24confirmation must be checked every day.
35:26Once the peak begins, we won't just
35:28look at the ad dashboard. On your daily
35:30dashboard, you should be looking at
35:31everything: ad spend, order revenue,
35:33post-ad contribution, successful
35:35payment rates, the number of pending
35:37orders, and available cash. Look, if
35:38pending orders are growing rapidly even
35:40though ads are profitable every day,
35:42the budget increase may need to be
35:43paused. If the successful payment rate
35:45drops while clicks and carts remain the
35:46same, investigate the payment system
35:48instead of producing new creatives. If
35:49sales velocity increases and days of
35:51stock reach a dangerous level, new
35:53orders must be addressed before
35:54increasing ad budgets. So, the question
35:56at the daily meeting shouldn't be "How
35:58many did we sell yesterday?" What is
35:59the point in the system that is
36:00limiting growth today? This is the
36:02question we need to ask. When
36:03approaching the delivery limit, the ad
36:05message is also changed. If the product
36:07will no longer arrive by a certain date
36:09, we shouldn't sell it as if it will.
36:11If applicable, a faster delivery option
36:13, a period-independent use angle, or a
36:14digital alternative can be implemented.
36:17If it is not suitable or you cannot do
36:18it, the campaign is slowed down in a
36:20controlled manner. This decision may
36:21cause a loss of a few orders in the
36:23short term. But taking an order that we
36:24cannot deliver is not really a sale. It
36:26is just a momentary revenue increase on
36:28the dashboard. It is taking a debt from
36:29the customer that we will have to pay
36:30in the future. The work does not end
36:32when that Q4 campaign peak is over.
36:34Look, returns, re-shipments, and
36:35payment disputes must be added to the
36:37actual cost table immediately. The
36:38revenue in the ad panel must be
36:39compared with the net money passing
36:41through the bank account. You need to
36:42recalculate the actual contribution.
36:44Each week, for the previous week, which
36:45creative worked solely because of the
36:47discount? Which one generated sales
36:48independently of the period? Which
36:49product sold well but generated a high
36:51number of support requests? Which
36:52package raised the average basket size
36:54but increased preparation errors? These
36:55answers determine the product and
36:57operational decisions for the next
36:58period. Q4 is not a magical period that
37:00saves a weak business. Look, it is a
37:01period that amplifies the strengths and
37:03weaknesses already present in the
37:04business. If our economy is broken,
37:06more advertising leads to more losses.
37:08If our payment system is problematic,
37:09more traffic brings more failed
37:11transactions. If the supply is not
37:13ready, more orders produce more delays.
37:15But if your contribution is calculated,
37:16the promise you made to the customer
37:18can be met by supply, payment and
37:20measurement work correctly, and your
37:21creative production is not tied to a
37:23single ad, then Q4 ceases to be an
37:25uncontrolled rush. It turns into a
37:26manageable growth area. Because Q4 is
37:28truly a period of opportunity. The
37:30first thing you do after this video
37:31shouldn't be to immediately build a
37:33store and prepare ads for that product
37:34you found. Open a blank page and write
37:36down these five numbers. What is your
37:37available capital? What is your
37:38contribution per order? What is your
37:40break-even customer acquisition cost?
37:42What will your cash conversion cycle be
37:43? And what will your daily operational
37:45capacity be? When these 5 numbers are
37:47ready, it makes it much clearer in
37:48which market and with what level of
37:50risk you can test that product. The Q4
37:52roadmap starts exactly here, but the
37:54biggest mistake you can make after this
37:55video is finding this system logical
37:57and staying in the same place tomorrow
37:59without knowing where to start. Because
38:01what most people lack isn't new
38:02information. It is the absence of an
38:04actionable roadmap showing what work to
38:06do, in what order, and with what
38:08materials. That is why you can sign up
38:10below for the completely free workshop
38:12we are hosting next month. In the
38:13workshop, we will share what to do each
38:16day in Q4, which materials you will
38:18need while doing these tasks, and all
38:20the files those materials will contain.
38:22You do not have to pay any fees. Not
38:24for the workshop, nor afterward. If you
38:27want to enter 2025 with your own store
38:29and an income-generating system, and if
38:31you want to set out without spending
38:33any money, just by dedicating your time
38:35, you can register for the workshop for
38:38free via the link below. See you in the
38:40workshop. Yeah.

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