This post is sponsored by Adchieve. The opinions expressed in this article are those of the sponsor.
Google Ads Smart Shopping campaigns offer a number of benefits that advertisers find attractive – particularly those that attempt to manage product promotion at scale.
It’s a form that makes Google’s machine learning work for you by automating bidding, testing, and ad placement, using your product feed to show ads across the Google Search Network, Google Display Network, YouTube, Gmail, and more.
They can be a useful aid in streamlining and streamlining campaign management – that’s for sure.
But having machine learning do the heavy lifting has potential downsides, too.
Smart shopping can be something of a data “black box” for marketers.
How can you use the different types of data available to you to best influence the outcomes of this machine-assisted automation?
Once you have a better understanding of the inputs and outputs of that black box, you can tinker with the inputs more effectively.
In this article, you will learn how to do this.
Read on as we explain how you can use the combined insights gained from different types of data to better match your business goals, generate the best possible ROI, and move the needle in product sales.
The unprecedented importance of data science
Before you can uncover insights, you must first understand the distinction between different types of data.
google data: The data you get from Google
Even though Google reveals less data than ever before, there’s still a lot of important information you can use. Think about conversions, costs, impressions, etc.
Company Data: Company-specific data indicating key performance indicators or factors you focus on
Company data is data that you own. Think of insights on margins, equity data, and all kinds of customer data.
Competition data: Data about what’s happening in your market
The third data source is data about the market in which you are active.
- Are you ahead or behind your competitors?
- What are your competitors’ prices and what products do they offer?
- What keywords do they rank for and you don’t?
Now let’s jump into ideas.
4 Examples: How turning data into insights can give you a head start
Different types of data are needed to gain valuable insights.
Sometimes this relates to insights for which you only need a single data source, but we think the best ideas can be found when you combine Google, company and competition data.
Here are some examples of the insights you can now generate with Adchieve to improve your Smart Shopping campaigns:
- Understanding Campaign Profitability (POAS).
- Insight into cross-selling and up-selling patterns.
- Insight into prices and their importance to your rankings.
- Insight into keywords in Smart Shopping campaigns.
1. POAS Insights
On our journey to understand Google’s shopping algorithm, we wondered if return on ad spend was a good goal. Return on ad spend is just a percentage that says nothing about your profitability.
What is the perfect ROAS where you generate big and healthy profits and returns? Should your ROAS target be the same for every product in your Shopping campaign?
This is why more and more advertisers are now using POAS (profit on ads spent) insights.
Where previously you only managed ROAS revenue, we can now get automated profit insights by integrating Google data (cost data) with company data (margins).
Here’s proof that a good return on ad spend doesn’t have to be a good selling point:
Read more about running and the benefits of POAS in this Adchieve article, Google Ads: Why Choose POAS Objective Over ROAS.
2. Cross-Selling and Upsell Insights
When developing POAS Insights, we also realized that advertising on Product A does not always mean that you are also selling Product A. but only product c.
This is why we developed the Product Advertising Contribution Model, where the central message is that advertising for Product A does not always lead to (only) selling Product A.
Here is an illustration of the product ads contribution model:
This is important when calculating your profit margin.
Product C can have a very different margin than Product A, and the sale of Product B can also be very interesting from the point of view of margin technology.
3. The effect of your price on the order
Do your prices affect your Google rankings? We wanted to discover if this claim was fact or fiction, so we set out to investigate.
For a major UK retailer, we have adjusted retail prices for a range of random products over a four-month period. The products fall into one of five price ranges around the standard price quoted by Google, and the prices were, for example, 15% cheaper one week and 5% more expensive the next.
We took into account movements within the benchmark itself, and for each product, the random price range of the product that week was determined. You can see the result in the chart below.
We’ve seen a clear decreasing effect in impressions. The products in the product group that had the most discount were shown most often and were clicked on most often.
Conversely, products that increased in price the most were viewed the least and clicked the least. Google shows you more when it’s cheaper, but the difference in conversion rate is much greater than impressions. So the price is important.
By providing insight into competitor pricing within Google Shopping, we provide a more accurate picture.
4. Keyword insights
We recently developed a tool that generates insights within Smart Shopping at the keyword level by collecting search term data both structurally and automatically through crawling.
This crawl data helps you understand what’s going on inside Smart Shopping. You can see the effects at the keyword level for:
- Adjustments in ROAS.
- Changes to your bid.
- The effects of improvements in your product scores.
- Address modifications.
- The effect of newly added products on your rankings.
Bit Group, Europe’s largest online lighting provider, also uses our advantage. With the returned keyword data, they can instantly improve campaigns or see the impact of adjustments.
Data is also strategically important because it allows them to closely monitor where they stand in relation to the competition (we call this “market share”). It also flagged bits of products that were popular on Google Shopping and those that weren’t in their range.
Learn more about the topic in this article: Back Keyword Insights for Google Smart Shopping.
Success factors for managing campaigns differently
In addition to Luqom and the large UK retailer, at Adchieve, we have conducted research over the past two years with other leading retailers on success factors for an algorithmic surfing app.
What we have learned is that four important precondition factors.
Be clear about your business goals
This may seem like a watershed point, but in practice it is much more difficult. You want to focus on improving your margin, but could that also be at the expense of your turnover?
Or do you want to grow in a specific market, for example, without losing sight of your sales volume / market share?
Knowing your goals isn’t just important for showing you where you want to go. It also affects the data you need and the structures you can best work with during your campaign.
It goes beyond the marketing department
Anyone who wants to get points in Google in the short or medium term should also think about its scope and the prices charged. For assortment matters, you need to involve the purchasing department or category management.
Want to provide insight into your sales margins across Google? Then you need experience from financial management.
As a PPC Manager or Internet Marketer, you work less in the Google interface and more with colleagues (from other departments).
Be open to experimenting and learning – not just taking direct action
PPC managers used to take a lot of action, for example, by adjusting bids and keywords directly. You can control far fewer buttons with Smart Shopping.
So, it is less about the number of actions you take but more about the quality of those decisions. What ROAS goals and campaign structure will help you achieve your business goals?
The above requires you to build new knowledge by keeping abreast of developments in the market, and also by experimenting yourself and learning what works and what doesn’t work in your situation.
Experiments don’t always lead to actionable items, but they do lead to interesting new insights that spark new considerations–helping you get closer to your goals.
This also requires commitment and involvement of a senior person in the organisation. This person knows the goals of the business, can think over and direct interdepartmental actions, can initiate experiments that have not been used or that have not been dared to lower in the organization.
Put it all into practice with the right software
Finally, you’re ready, and there’s a commitment from someone higher up in your organization.
Using data-driven ad automation software means you can act on your insights and manage your campaigns differently – and not just feed Black box, but in our words, “black box color.”
What will you have insight into?
- You can make proven changes to your campaign’s return on ad spend.
- You can expect the impact of the ROAS adjustment on both revenue and margin
- Based on your keyword insights, you can estimate how much space is left to win positions on important search terms.
- Have insight into your content and how it is ranked.
- You can see what content your competitors are using (headlines and images) and whether they rank better with it. Based on that, you can make documented edits to your content.
- What are your best rates? At what prices do you have the largest margin but also rank highest within Google? Combined with cross-selling and up-selling insights, and using keyword data, you can come to interesting conclusions.
And finally, how cool would it be if you could even influence your product range?
Based on the insights we provided through Adchieve, Lokmat has expanded its reach within a rating by 50%.
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Featured image: Shutterstock / fatmawati achmad zaenuri