Google enters the dropshipping business
If you have been following our daily briefing, you might be well aware that Amazon is chipping away product searches from Google over the last few years. Google had to do something about it, right?
They did it! Google has announced the rollout of Shopping Actions on its Shopping portal.
+ Quick Summary: Shopping Actions will enable users to buy products from various retailers right within Google Shopping. Once the payment is made, the retailers will handle the rest of the order logistics. Google will take an undisclosed cut off each sale.
How will it work?
So far, Google Shopping primarily worked as a comparison engine. Users searched for products on Google and compared offers from different retailers. When users clicked on any product listings, they were taken to the retailers’ website to finally buy the product and make the payment.
But now, with Shopping Actions, users will be able to add products from participating retailers to a Google Shopping cart and check out using the payment method stored in their Google accounts. All this, without visiting the retailers’ website.
- Shopping Actions will work across all Google’s product searches, mobile shopping, cross-device transactions and voice search initiatives.
- Target, Costco, Sephora, Nike are among the hundreds of retailers participating.
- It will first be rolled out in France over the next few weeks. It’s not clear when it will extend to other markets.
- It’s built on the Google Express product that provides shipping incentives, personalized recommendations, loyalty program credits and universal checkout.
“We are not becoming a marketplace like Amazon” – Google!
Google has clearly stated that the company does not want to become a retailer the way that Amazon buys and sells inventory, sets price restrictions on sellers and handles fulfilment logistics.
That is the main distinction it wants to try to make: Google is the retailers’ friend.
Platform-as-payment-facilitator is not a new concept. Amazon started similarly and is now accountable for nearly 50% of product searches. Instagram is already working on in-app checkouts. All of this will have a dramatic impact on e-commerce.
Plus, retailers will now have to factor Google commissions into their margins, just as they do on Amazon and will soon do with Instagram.
Platform-as-payment-facilitator might be a huge game changer in e-commerce. With all the giants entering the market, only time will tell which way the pendulum is going to swing.
Spark Network SE acquires Zook Inc.
Are you in the dating niche? This piece of news is probably for you. It won’t influence your campaigns per se. But it’s something you might be interested in.
Ever heard about Spark Networks SE? It’s a leading global dating company with a big portfolio of online dating services. LDSSingles.com, EliteSingles, Attractive World, Jdate and Adventist Singles to name a few.
They have plenty of affiliate offers. And if you indeed are working on this niche, you probably know some of the dating services they own.
But what’s the news?
Spark Networks SE has announced its entry into a definitive agreement to acquire Zoosk, Inc.
Zoosk, Inc is one of the strongest dating apps in the North American market, which comprises half of the $5B global online dating market. It seems to be a good move for Spark Networks SE.
Data. Data. Data. How much does it matter?
We are talking about marketers’ favourite thing: DATA. Wait, your next favourite thing after WHAT THE AFF… Humble of us to think that, we know!
We hit this topic in two ways to satisfy all our readers: whether you’re just starting your journey or you’re a data aficionado, you might want to go through this.
The easy way to test offers
According to Charles Ngo, the offer is what can make or break your campaigns. Thus, testing different offers to find the best-performing ones is highly important.
How to conduct the right tests? There isn’t an exact amount of days or budget you need to run a test. Every combination of offer/angle/audience is different, thus every test is different.
Whether new or seasoned media buyer, making sure that your data has statistical significance is very important.
Charles suggests using this calculator because it’s very simple to use and it doesn’t have too many unnecessary options.
So, if you’re running a test, and you don’t know which is the best offer, you can refer to this calculator to find the best one. You’ll just have to insert your clicks and conversions data in the “Visitors” and “Conversion” sections.
And for every offer, you’ll need to add a new Treatment.
Once you have added the data, calculate the confidence interval, that is the probable percentage that you’re headed in the right direction.
The ideal percentage is 95%. But when doing a test, you can have three scenarios from it:
- Not enough data: If the confidence interval is much lower than 95%, it means that you don’t have enough data to make a decision. Keep the test running.
- Too much data: If the confidence interval is higher than 95%, you will know which offer is the best, but you might have spent more money then needed to conduct a test.
- Right amount of data: If the confidence level is around 95%, you have just enough data to find the best offer.
That’s about it. If you have been reading our emails regularly, you know that testing is the only Marketing God we trust in.
Therefore, we thought that bringing you this post from Charles Ngo and this easy-to-use calculator might be helpful for your endeavours. Even if you’re an experienced marketer or just starting your journey.
PS: You can use this for every sort of test, not just offers. Whatever test you’re running, statistics will tell you if you have enough data to make decisions.
Use data to make more accurate predictions: Regression Analysis
As an advanced marketer, you are expected to go beyond what everyone else is doing, to find new ways to stand out from others. And to be able to make better data predictions.
Ever wonder how Facebook, Google ad platforms provide you Reach, Conversion estimates based on your current settings/data?
What are we talking about?
Regression Analysis. It involves basic machine learning (ML) and a simple mathematical application to help you make better predictions from your data. Well, beyond educated guessing.
Sounds scary? Well, it’s not really that complex. Besides, we will go through it step-by-step to make it even easier and at the same time, extremely useful for you.
Let’s see how you can use regression to predict the conversion volumes you can achieve by adjusting your campaign spends.
A regression model is just an algorithm which creates a line or a curve based on the data you feed it. And using this graph, you can make predictions to explain the relationship between different parameters. Such as Cost vs Conversions, Cost vs CPA etc.
To give you a visual example below, this regression model predicts that if you spend $4k on ads, you should make about 40 conversions.
How to build Regression in 5 Steps
- Step 1: Prepare the data. Open a spreadsheet. Paste your “Cost” data in Column A and “Conversion” data in Column B. If you downloaded this data from somewhere, remove all columns except “Cost” and “Conversions.”
- Step 2: Generate Scatter graph in Excel. Select the data under “Cost” and “Conversions” columns. From the menu bar, select “Insert”–> “Charts”–> ‘Scatter Graph”.
- Step 3: Create a regression line in the Scatter graph. Right-clicking on any of the data points (blue dots) and select “Add Trendline”.
- Step 4: Choosing regression lines using R-squared (R2). On the right-hand side menu, you will now see different “Trendline options”. You can start by selecting “Logarithmic”. “Display R-Squared value on chart”.
PS: The higher the R2 value, the better the fit of the line. As you go through different regression lines (Trendline options), you can view which has the highest R-squared value. You can also decide visually which appears to fit best.
Step 5: Add the regression formula for the fit you have chosen. To do this, check the box named “Display equation on chart”. We will use this formula to make predictions.
Voilà! You have generated the formula. Based on the historical data used for this regression analysis, you will have a formula which looks something like y = 28.782*ln(x) – 190.36. Where x = cost and y = conversions.
To predict y for any given x, all you gotta do is replace x with a real number.
Let’s say you want to predict the number of conversions for a daily ad spent of $1k. Replace “x” in the formula above with 1000. Using a calculator, it comes out to around 8 conversions per day.
You don’t even need a calculator. Simply enter the formula in Google search and Google calculator will automatically give you the results.
You can use the same method to even create a CPA vs Cost graph to predict the number of conversions at your desired CPA.
PS: This only works accurately with historical data. So, if you expect any fluctuations in your campaign performance in future because of an upcoming sale or a new offer, that will not be taken into account. Hence, only take more recent and realistic data to come up with accurate predictions.
Want to learn more about it? Head here for the detailed steps along with screenshots.
It’s a divorce
If you’re in the e-commerce space and a Shopify user, you probably have heard about this: Mailchimp won’t be available as a Shopify integration anymore.
So, if you have been using MailChimp for abandoned carts, driving upsell, nurture leads and other email stuff, you have until May 12.
From that day onwards, MailChimp and Shopify are ending up their relationship.
But let’s hear what both sides have to say about:
Shopify declared that “they had concerns about Mailchimp’s app because of the poor merchant experience and their refusal to respect our Partner Program Agreement.”
“Mailchimp refuses to synchronize customer information captured on merchants’ online stores and email opt-out preferences. As a result, our merchants, other apps, and partner ecosystem can’t reliably serve their customers or comply with privacy legislation.”
MailChimp, on its side, has a different point of view: “We have asked Shopify to remove the MailChimp for Shopify integration from their marketplace […] because Shopify released updated terms that would negatively impact our business and put our users at risk.”
Moreover, MailChimp added that they’ve been negotiating for months in order to find a deal that would be fair for both sides. Apparently, it didn’t end up in a friendly manner.
We’ve got two companies that both argue that they are just putting their customers’ privacy first. The conflict didn’t end in the best way. But the most affected are their users because it’s on them to find a solution.
Looking for another email service provider, migrating the lists, the data, and everything else to another platform is a time-consuming task.
Maybe this experience makes Shopify create (or buy) their own email service. Plus, it can be another source of income for them… All in one unified platform.
Pinterest goes public
Lately, Pinterest has been occupying enough space in our daily briefing. Its user base is growing and its ad platform is being adopted by more marketers than ever before.
This time, it’s about their IPO. In fact, the company is preparing to debut on Wall Street.
2018 stats show that the company has 250M monthly users and a net loss of $63M. Not a big loss compared to the loss of other startups preparing to go public. Uber, for instance, previously disclosed that it lost $842M in Q4 of 2018 alone.
Pinterest will bet hard on e-commerce and they claim they are going to be a more shoppable platform to turn that these losses into positive margins.
It means that Pinterest will be competing with e-commerce giant Amazon and giant-in-the-making Instagram. A very tough challenge.
However, Pinterest says it has a competitive advantage: It captures the attention of consumers when they’re looking for inspiration for their wardrobe or still mapping out an idea for a specific DIY home project.
Will this be enough to attract advertisers’ budget? Only the future will tell.
Why you should care
Pinterest has a clear idea: Expanding into the e-commerce industry. Will they have enough trust from the market with their IPO? If so, there will be new capital to feed the company’s growth and bring a better experience for advertisers.
Cool tech, (funny) business, lifestyle and all the other things affiliates like to chat about while sipping cocktails by the pool.
They won’t notice a few mill’ missin’
How stupid do you think Google or Facebook can be? Or how smart or plain lucky can someone be?
A man from Lithuania stole $99M from Facebook and $23M from Google between 2013 and 2015. Just by sending them invoices for items they hadn’t purchased and that he hadn’t provided, which the companies paid anyway. WHAT THE AFF!
These fake invoices just appeared to be signed by the executives of these companies with fake corporate stamps.
Apparently, no one from Facebook and Google bothered to check first if these invoices had actually been issued within the company and simply released the payments by wire transfer.
Is there any surprise that both companies have issues with enforcing their own advertising policies?