How to make your Google Shopping campaign a winner

As the field becomes ever more sophisticated, here's how think like an e-commerce specialist and stay ahead.

How to make your Google Shopping campaign a winner

Liam Patterson, CEO and founder at Bidnamicunveils some advanced techniques marketers can use to boost their results…

E-commerce marketers are constantly challenged to generate more growth or improve margins, or both… and in a climate where competition is increasingly global and sophisticated, and powerful.

Google Shopping is no exception. By the end of 2020, for example, Amazon accounted for over 50% of impressions in some sectors.

There is also a growing long tail of SMEs with digital storefronts, thanks to ‘plug in and play’ technology platforms like Shopify and Magento, and larger enterprises are being enticed off legacy in-house platforms by the likes of Shopify+, BigCommerce, and factory-to-consumer outsources solutions from THG Ingenuity, for example.

So how to compete? Marketers need to adopt the mindset of the new generation of e-commerce specialists and deploy data, algorithms and insight to establish a sustainable competitive advantage.

1. Ditch averages, embrace precision

No matter your industry or product, every stock-keeping unit (SKU) is completely unique. At any given time, each SKU has its own ‘true’ bid value – an exact price that captures the click at the right cost for your business.

The problem is that even a small number of products can generate hundreds, or thousands, of variables, and calculating a bid value for each SKU becomes impossible.

Recommended best practice to overcome this manually is to use group bidding – group together SKUs based on product, brand, size, or some other attribute, and to calculate a bid based on the average cost per click (CPC) for the group.

Whilst this approach helps to address complexity, the fact that group bidding works on an average CPC value means that some bids will be too high and some will be too low, and the campaign will only ever generate average results.

To generate better than average results, e-commerce businesses need to ditch averages and embrace a precision bidding approach to Google Shopping, using automated bidding technologies to place the right bid at the right time against the right search term.

2. Bid based on product or customer profitability

Precision bidding goes far beyond colours or size ranges. Each SKU can have a different conversion rate, generate different average order values, attract customers with different lifetime values, and have different profit margins.

The default automated bid strategy choices in Google’s Smart Bidding include cost per acquisition, return on advertising spend, conversion numbers, or conversion value. Relying on these options leaves you vulnerable to wasted ad spend as well as missed opportunities to win converting traffic.

Using a more advanced metric like Cost of Goods Sold you can calculate accurate bids based on the profitability of each SKU in your catalogue, which means you can afford to bid more aggressively for popular search terms whilst maintaining a healthy ROAS.

Similarly, adjusting bids based on the lifetime value of customers who bought that product previously means you can bid higher in the knowledge that any fall in short-term ROAS will be more than covered by future purchases from the new customer.

3. Target the most valuable search terms

Not all search terms are equal, however those familiar with Google ads will know that – ordinarily – search term targeting isn’t possible for Google Shopping campaigns. 

Whilst its ‘black box’ approach doesn’t let marketers see which search terms are generating the best results, Google’s Smart Shopping platform addresses this need by automating the bidding process, working 24/7 to achieve the ROAS or CPC goals that are entered into Adwords.

Other automated solutions exist for marketers wanting to retain access to granular data, such as Bidnamic’s machine learning platform which provides valuable search term data that can help optimise other channels and adjust stock levels based on changes in demand.

4. Use your search term data to personalise landing pages

Granular search term data also provides great opportunities to optimise other stages in the customer journey. Advanced merchandising technologies, for example, can use search term data to dynamically adjust the landing pages in your store, depending on the search term used.

Platforms like Nosto can utilise this search term data not just to increase the conversion rate for that SKU but to promote related products based on data from previous purchases, increasing the average order value, and in turn allowing you to bid higher on the specific search term.

We all know that a sustainable approach to e-commerce involves increasing automation. Marketers looking to cut-through, grab consumer attention at the right moment and convert intent into profit need to adopt innovative technologies to compete. In this journey your data is your best friend and most valuable asset – across all your channels, not just Google Shopping.


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