The [email protected] event in Dublin was an opportunity for ecommerce advertisers and agencies to meet with Google and discuss challenges and opportunities facing pureplay and multi-channel retailers.
The event, split over two days, broadly covered a number of aspects including trends in technology and usage, the mobile landing page environment, performance branding, effectively managing the upgrade process from Product Listing Ads (PLAs) to Shopping Campaigns, and audience segmentation for remarketing. Speakers ranged from the Director of Retail (EMEA) to Industry Managers, Product Specialists, and Account Strategists.
Whilst each topic could be covered within this post, I’ve chosen to apply an in-depth focus on the most pertinent to ecommerce advertiser’s needs at this precise time - namely, how to effectively and efficiently manage the transition from PLAs to Shopping Campaigns.
This is a particularly important issue to retailers, as PLAs have superseded text ads as the format of choice within the ecommerce vertical – indeed PLAs have been found to drive a 22% higher Click-Through Rate (CTR) than traditional text ads. Moreover, these are appearing to become more mainstream amongst advertisers, as over half of those who were attending the event had at least some exposure to PLAs.
Making the most out of Google Shopping: Implementation and benefits of Shopping Campaigns
Google announced Shopping Campaigns last year, as a new way to build out PLAs. Ultimately, Shopping Campaigns streamline the way users structure their campaigns, bids and reporting – the main difference between the two is that Shopping Campaigns are built around the concept of sub-groups, whereby layers are created in order to split out specific products based on high value segments (i.e. best sellers, brands and promotions).
The main benefit to this, Google proclaimed, was that ad spend could easily be diverted to those areas where it offered the best return. As with conventional AdWords campaigns, granularity is key, and a more granular approach to structure allows for more accurate reporting and more effective account-wide optimisation.
Upgrading to Google Shopping Campaigns: Why make the change?
Taking a step back, Google will automatically upgrade PLA campaigns to Shopping Campaigns in August 2014, during the event they defined the benefits of upgrading early – namely leveraging learnings from Shopping Campaigns quicker than competitors, and to take advantage of the reporting tools that this new campaign type can offer.
For example, advertisers can now pull out reports which focus on benchmarking CTR and Impression Share against competitor averages. Cynics might suggest that Google have released this new functionality for financial gain (i.e. greater visibility of competitor bidding practices would facilitate higher bids), but it is actually genuinely useful as it provides greater visibility to help make more informed bidding decisions.
Google also emphasised that retailers must ask themselves several questions in order to flesh out their upgrade strategy. For example, if the existing PLA structure contained considerable history, or was already broken out by product or performance attributes, then upgrading a few campaigns at a time was seen to be the more beneficial approach – this makes sense and certainly echo’s our practices, where we look to leave the most mature campaigns until last.
But what if the existing campaign structure was less mature, and campaigns contained mainly ‘all products’ ad groups? In this scenario, retailers are better off upgrading their entire portfolio of PLA campaigns – or at least create Shopping Campaigns to run side-by-side with PLAs in order to build up history.
Data feed quality: Why it matters
Data feed quality is another (and perhaps the most important) element of Shopping Campaign success. Whilst the system is still relatively immature (PLAs have only been around for a year), it needs information to survive and prosper - in other words, to increase relevancy.
In order to achieve this, it relies on product data feeds to supply accurate and comprehensive information on products. Jellyfish take feed optimisation very seriously, and a great deal of time is spent on ensuring that every feed abides by our optimisation methodology, which is based on Google best practice.
From the event, the advice to retailers was clear – look beyond the recommended fields within the data feed and populate as many fields as possible, the more comprehensive the detail the better. Mostly common sense stuff, and taking this a step further, the value of quality imagery was also highlighted – fundamentally Shopping Campaigns are a visual experience, and this point is where a lot of retailers fall short. Use of uninspiring, low-res, or watermarked imagery are common mistakes which will return only low CTRs and missed opportunities on these highly competitive search landscapes.
Title descriptions are also a key element of feed optimisation, and the importance of accurate and clear language cannot be down-played. The premise for title optimisation is clear – as Shopping Campaigns don’t utilise keywords, strong titles mean better query matching. The main recommendation here was to be wary of truncation, as titles are often cut off – indeed, front loading text to fit with search context was suggested as a key way to improve CTRs among Shopping Campaigns, as users were more likely to be drawn to ads which reflected search queries before truncation took place.
Another key insight that we utilise time and again is to look at search query data to see exactly how users are structuring their searches across product categories, and adopt this approach within title descriptions.
A final point on titles and descriptions - it’s easy for advertisers to fall in the trap of utilising ‘unique’ colours, such as apple, fuchsia, or topaz. In such instances, ads are less likely to match, so it’s important to ‘normalise’ your descriptions so that a) Google actually displays your ad, and b) the likelihood of a user clicking on your ad increases, as the ad title is better matched to the original search query.
Google also briefly touched upon additional aspects of the new Shopping Campaign structure. In the old PLA format, products could be spread across multiple campaigns and ultimately the highest bid determined which was shown.
Now, campaign priority settings are utilised to control which campaigns should supersede others in terms of importance. So a product in one campaign with a bid of £1.00 could be superseded by a product in another with a lower bid, as the second campaign has the higher priority.
Retailers may be drawn to this feature in order to try and control the serving of lower margin products vs. higher margin products. We adopt an approach whereby campaigns are segmented based on ROI levers such as seasonality, best sellers, and core products (i.e. everything else). This allows us to distribute budget to better-performing campaigns, and the campaign priority setting is invaluable as it allows us to prioritise products within the 'bestsellers’ (highest priority) and ‘seasonal’ campaigns over the ‘core’ campaign (lowest priority).
By segmenting in this way, retailers can minimise the possibility of better-performing products being suppressed by others, much like within keyword-based campaigns where top-performing terms are split out in order to drive incremental volume and maximise efficiency.
All in all, this session was a useful reminder to advertisers about the benefits of upgrading early to Shopping Campaigns, and also that top-line optimisation across product feeds was critical to Shopping Campaign success. On the day, Google recommended that retailers:
- Upgrade early to see the full benefit of Shopping Campaigns
- Split out products based on high value segments
- Submit clean and clear data, with all attributes
- Utilise ‘glamour’ shots for images
- Optimise titles for better query matching
- Normalise language
- Categorise accurately
I’d also add the following in order to get the best out of Shopping Campaigns:
- Start soon, and start slow – it’s easy to get caught up and get granular too quickly. Don’t over-complicate things at first, and split out based on product performance.
- Don’t ignore the search query data, it can help provide valuable insight into the structure of searches – which can help to optimise your data feed.
- Analyse your data to ascertain performance trends around time of day and schedule activity to suit.
- Split out campaigns based on ROI levers, in order to get the most from this new structure.