Targeting your entire country/region with the same ad, and the same landing page, whilst assuming the results and user behaviour will be the same isn’t logical. We believe that segmenting your targeting, ad copy and landing pages by location is a sure-fire way to drive up conversion rates. There are a number of reasons why:

1. Efficiency – All locations are not equal. Areas vary wildly in terms of wealth, demographics, politics, and many other factors. It follows on that the value of conversions will not be equal between locations either. As a result, splitting out locations will help with budget allocation and target setting. In theory, most advertising platforms will apportion traffic to locations based on one overriding target. However, this only applies when a business has a single objective, which is not that common.
2. Brand Awareness – Click-through rates and conversion rates will inevitably be lower in regions where a brand is less known. This creates an opportunity to grow the brand in specific areas with messaging targeted to users in the discovery phase. Conversely, spend could be pulled in these areas to focus on short-term performance.
3. Ad Relevancy – Inserting locations into ad copy will increase ad relevancy and boost engagement. At a basic level, key locations can be split out manually and inserted into headlines, descriptions and other content.

Taking Localisation Further

In Google Ads, dynamic location parameters can be inserted into ad copy, and then pulled through to landing pages, meaning messaging can be customised throughout the user journey. In our experience, there is a use case for testing this for all businesses:

1. Brick-and-Mortar Stores – The most straight forward use would be for brick-and-mortar stores. Showing the user their nearest store, its opening times, and directions means multiple steps in the online journey can be removed.
2. Online Lead Generation – Businesses without physical locations can still benefit from localised copy on their landing pages. This can take the form of relevant statistics to the area e.g. “We’ve sold 56 houses in BS5 this month”, local business testimonials, or area specific headlines e.g. “Financial Advisors in Birmingham”. Developing trust for an entirely online service can be difficult, but adding local information will help.
3. Ecommerce – Arguably the type of business where location specific language is least relevant is ecommerce. However, there are a few cases where location specific landing pages should be tested. For example, delivery offerings. If the delivery service is particularly good in certain areas, shout about it. Secondly, there may be some specific cases where location has a bearing on suggested products, or even available products for delivery.

A Final Note

If you are implementing location targeting and messaging across your digital offering, there are a few keys things to remember. Firstly, make sure everything you track about the user is compliant with GDPR and relevant cookie laws. For localised landing pages, always A/B test against a control page first, and ensure you have backup headlines if dynamic parameters fail to pull through. Finally, don’t be creepy – Localisation is great, but not everyone wants to know how many steps your business is from their front door!

The post Leveraging Local Advertising for Online Brands appeared first on Grapevine.

Despite its potential, adoption of the feature has been slow; likely due to a lack of technical know-how or concerns about cost. Even those who have set up the connection are often not utilising it to its full potential.

The BigQuery integration can be a game-changer for businesses, providing several benefits that are not available in the GA4 reporting interface. Here are a few reasons why you should be using BigQuery today:

Soup Up Your Looker Studio Reporting

Have you noticed that your Looker Studio GA4 reports have started to break? Google recently introduced analytics data API quotas, which have impacted even the most basic reports. If your report is still intact, you may have to deal with poor performance and lots of buffering.

BigQuery’s connector for Looker Studio allows you to create GA4 data visualisations that won’t break and won’t buffer. What’s more, the connector actually queries the underlying dataset using SQL, so you don’t need to know any code to get started.

Eliminate Sampled Data and Cardinality

As has always been the case with Google Analytics, filtering large datasets leads to data sampling. With BigQuery, you have access to the raw data, so your reports will always be unsampled. This means you can draw more accurate conclusions.

Cardinality is also an issue in GA4. If a dimension can take many unique values, GA will often group several of these into a new value called “other”. This means the tables you view in GA4 are not always giving you the full picture. Using BigQuery eliminates this problem completely.

Aggregate Data From Multiple Sources

As a data warehouse, you can use BigQuery to aggregate data from many disparate sources. You can combine your GA4 data with data from your CRM, and start seeing how marketing activity really affects key business metrics, such as customer retention and profitability.

We are leveraging this feature for a number of our clients, to conduct some advanced lifetime value analysis. This simply wouldn’t have been possible without GA4’s integration with BigQuery.

Get rid of your costly marketing data hub

The integration of GA4 with BigQuery is a cost-effective solution for marketers. As compared to other data storage hubs that may require hundreds or even thousands of pounds per month, BigQuery offers an almost free alternative. While other platforms may still have their use cases, if your primary focus is analyzing Google Analytics data, switching to BigQuery can significantly reduce your costs.

Retain Your Data Forever

GA4 only retains some data for a maximum of 14 months (or two months if you haven’t changed your data retention settings). In BigQuery, your data is stored indefinitely, which is vital for longer-term reporting and data analysis.

What’s Next?

Setting up and using GA4’s BigQuery export is a fantastic way to get more from your marketing data, but it isn’t the most straightforward process. If you need any assistance setting up a BigQuery export from GA4, don’t hesitate to reach out for help.

The post Why You Should Be Using the BigQuery Export for GA4 appeared first on Grapevine.

My recommendation to clients was always this: Why bother installing Google Ads conversion tracking, when you can simply import your conversions from Google Analytics?

It seems like the obvious choice. The import feature is simple and works seamlessly, so why would you install two separate sets of tracking tags, when you can do everything with Google Analytics?

There are some notable benefits of this method of conversion tracking too. By using Google Analytics tracking in Google Ads, you can be sure that you are reporting using a consistent method of attribution. This is especially useful if you are using GA as your primary reporting source for your cross-channel marketing efforts. It’s also true that Google Analytics tracking is the most accurate for channel-agnostic reporting, as many of the ad platforms will claim 100% credit for conversions they only had a small hand in.

Despite the benefits of the GA import, Google Ads conversion tracking will definitely improve the performance of your ad account, and here’s why.

Last Google Ads Click vs Last Non-direct Click

The main difference between the two methods of conversion is the attribution model. Google Analytics uses a last non-direct click model, which means a conversion is attributed to the last touchpoint in the journey before conversion (except if that touchpoint is direct). For example, a user who visits a site via a paid ad, and then returns via an organic listing before converting, will give 100% of the credit for the conversion to the organic listing.

Google Ads’ attribution model will look for the most recent Google Ads click and will give credit to that click. This means that in the example above, Google Ads would claim credit for this conversion.

In the days of cookie opt-ins and GDPR, the more data we can gather the better. Why would we only pass last-click conversions through to Google Ads, when we could be capturing every relevant conversion? After all, the automated bidding strategies can do the heavy lifting in terms of account optimisation, and feeding in more data will make those strategies more efficient.

Attribution models in Google Ads make no sense with GA tracking

Google Ads first started suggesting the use of their attribution models years ago. Models such as time-decay, position based, and the crown jewel data-driven attribution, have become a staple of most paid search strategies.

The thing is though, these models mean next to nothing if you are only sending last-click conversions through to Google Ads. Think about it this way – how can Google Ads attribute credit to any earlier click, if non-paid conversions are never being sent to the platform?

The result is, an attribution model that can only credit earlier clicks, if the last touchpoint before conversion is either a Google ad, or a direct visit. So much for intelligent attribution!

With Google Ads conversion tracking, all relevant conversions are ingested by the platform, and attribution modelling can work to its fullest extent. As with smart bidding, this means Google Ads will be optimising your account correctly.

Cross-device tracking and website call conversions

The main reason for switching to Google Ads conversion tracking comes down to attribution: more tracked conversions, more mature data, better account performance and results.

However, as if that wasn’t enough, Google Ads also throws in a couple of additional features that prove really useful. The first is cross-device tracking. Google Analytics cannot track conversions over multiple devices, but Google Ads uses a combination of data from signed-in Google accounts, and a healthy dose of modelling, to report on conversions that span more than one device.

Secondly, call conversions & Google’s call forwarding feature are only possible via Google Ads. Google dynamically changes your site’s phone number to a Google forwarding number. When a call is connected, Google Ads can report on this. You can even change the settings for different lengths of calls, if you want to qualify your leads. This tracking also works for call extensions within ads, which would never be tracked via the website.

A final word

Google Analytics tracking definitely has its place. It’s still the most robust way to measure your site’s performance across every channel, and should form the basis of any website performance reporting.

Within the Google Ads platform though, why not give some fit for purpose conversion tracking a go? We’re confident you’ll see results!

The post You aren’t reporting conversions correctly in Google Ads. Here’s why appeared first on Grapevine.

With Google recently announcing the sunsetting of Universal Analytics, now is the time to get to grips with GA4 attribution, and what it means for your business. If you want to read our thoughts on the positives and negatives of GA4, you can do so here.

Universal Analytics – Last click till we die

For the entirety of its 10+ year lifespan, only one attribution model was available in Universal Analytics – last non-direct click. Last non-direct attribution works by giving credit to the last user touchpoint before a conversion, unless that touchpoint is direct, in which case the touchpoint before is used etc.

In practice that means the following: Let’s say a user clicks on a paid ad, then an organic listing, and then converts. The organic listing receives 100% of the credit for the eventual goal or sale. That hardly sounds fair in today’s multi-device, multi-touch world. Luckily, Google have taken this into account, and have finally brought out proper attribution modelling with their newest product GA4.

GA4 – Attribution front and centre

Not only is last-click attribution now one of several options in GA4; it isn’t even the default. In its place, we have the new Cross-channel data-driven model.

Let’s see what Google have to say about their newest model:

“Data-driven attribution distributes credit for the conversion based on data for each conversion event. It’s different from the other models because it uses your account’s data to calculate the actual contribution of each click interaction.”

Not convinced? Let’s unpack what that actually means.

What Google is doing, in their own words, is “algorithmically assigning fractional conversion credit to marketing touchpoints”. In essence, Google examines all session paths of both converting and non-converting users, to see which paths are most likely to convert. Paths are then compared against one another for small changes that impact conversion rates. Additional signals such as time from conversion, device type, ad interactions, order of ad exposure, asset type etc. are also used to inform conversion probabilities.

Here’s a simple example. Google analyses that your site has a conversion rate of 3% for all users that click a paid ad, and then a social media post. Conversely your site has a 2% conversion rate for users that click a paid ad, and then an organic listing. The 50% uplift is then attributed to social media, with the result being social media deriving higher conversion value than organic across all relevant conversions.

Other attribution models are available

Google Ads users will be familiar with the other available attribution models. Position-based, time decay and first click models are all available, although the use cases for these are probably quite narrow.

If you really want to make your Google Analytics data match your Google Ads, you can also use the ads-preferred last click model, which is the model Google Ads has used for years. This model simply finds the last Google Ads click, and apportions 100% of the conversion to that click.

What attribution will mean for your business

We all know that users do not convert in the seamless way we’d like them to. Last click attribution is no longer fit for purpose, and I for one am glad we are seeing a shift in focus from Google. The hope is that better attribution and modelling will lead to less wasted marketing spend across the whole funnel. Google Ads will handle the change automatically, and begin to optimise your campaigns to modelled conversions. Third-party platforms will need manual intervention, but the data coming out of GA should be more representative of the real-world value of these platforms. In theory, that will mean more efficient marketing campaigns.

The Google black box gets bigger

My major concern with the new data driven attribution settings (and this same concern goes for most of Google’s recent updates) is that they are taking power and visibility away from the user.

You will never know how Google decides to apportion conversions in your account. The optimist in me hopes that Google’s intelligent data models and machine learning will make your reporting more accurate than ever; finally giving the correct credit to early funnel interactions.

The sceptic in me realises that Google have always used their analytics platform as a means to make more money via Google Ads. Don’t be surprised if data-driven attribution apportions more conversions to your Google Ads account, and, when combined with automated bidding strategies, leads to increased spend.

The truth is, Google is automating more and more of the marketing process whether we like it or not. Most of that automation has proved to be beneficial, and I’m sure better attribution modelling will help businesses meet their goals. The trouble is, even if it doesn’t, you won’t know a thing about it!

The post GA4 Attribution Settings appeared first on Grapevine.

Like it or not, GA4 will be the default analytics product moving forward. Google recently announced that they will be sunsetting UA in July 2023, and given the reception to GA4 in its first years, I’m sure this announcement was not positively received by many marketers.

It’s not all doom and gloom though. GA4 comes with some notable improvements, which could be transformative for your business’s data collection and reporting. In this article I’ll be unpicking the good and the bad, so you can decide which analytics product to use over the coming months as you transition to a GA4 only world. Spoiler – it’s both!

Pro – Combined app and web view

Gone are the days of having two sources of data for your web traffic and your app traffic. GA4 was built with cross-platform tracking in mind. The new event-based data structure in GA4 is perfect for handling hits from both webpages and applications, and even the terminology used in the platform is more universal to accommodate both types of measurement.

After installing a consistent user ID, you’ll be able to stitch your users’ web and app sessions together, giving you even more insight into user behaviour. If you have significant app traffic, GA4 will definitely be the platform for you.

Con – No more hierarchical events and strict parameter limits

Many publications and blogs I’ve read have talked about the positives of the new event data model. I’m not so sure. For the everyday drop-in and drop-out analysis that most marketers undertake, the hierarchical structure of event category, action, and label was a simple one to understand.

My major gripe though, is the lack of parameters allowed with the new model. Only 50 event-scoped custom dimensions can be registered in a GA4. While only 20 custom dimension slots were available in UA, the event structure actually allowed you to send unbounded information into the event reports. The new data structure is far more limiting.

It’s now crucial that you map out your analytics solution, so you don’t run out of space in GA. Decide ahead of time which dimensions and metrics you wish to measure, and make sure you aren’t sending any data into GA that is redundant, or not useful for your reporting.

Pro – BigQuery integration

The BigQuery integration for UA would have set you back $150,000 a year – hardly a snip. The same integration for GA4 is now completely free. The BigQuery data warehouse gives you the ability to join your GA data with offline data sources, such as your CRM. If you’re really smart, you could even run your GA data through statistical models, or develop your own attribution method. Whilst complex, the benefit for medium to large organisations is marked.

Con – Fewer predefined reports

The in-built reports in GA4 are by far its worst feature. The overwhelming positive of UA were the predefined reports that provided so much value for so little effort. The majority of that reporting has been stripped back, and in its place we have been presented with Analysis Hub. The Analysis Hub allows users to create their own reports, by combining dimensions, metrics and segments in whatever way they wish.

The problem is we used to get 80% of the reports we needed without having to configure them. Now almost every report you want will have to be built from the ground up, which could be a big time sink. Framing this in a more positive light, GA4 forces the user to become more data literate, by making them define their own reports. Maybe this will be a good thing in the long run.

Pro – Intelligent audience creation

For the day-to-day analytics user, this is the feature to focus on. Firstly, I want to talk about audience triggers. With an audience trigger, you can now fire an analytics event every time a user is added to that audience. This means you can create complex audiences and easily monitor how many people are matching that pattern of behaviour.

Secondly, predictive audiences. Predictive audiences use GAs machine learning to predict the future behaviour of your users. This allows you to create audiences such as ‘Likely 7-day purchasers’ or ‘Likely 7-day churning users’. The latter is particularly important for re-engaging iOS users who might otherwise have their GA cookies wiped from their Safari browser. I envisage that predictive audiences will be a cornerstone of any good remarketing campaign in the years to come. Google’s algorithmic power is getting better all the time, and tapping into it will be key.

Con – No views

I’m a major believer in creating useful views in GA, as they help to keep your data clean and orderly. Well configured Universal Analytics accounts should have a view for reporting, a staging site view, a raw data view, and a test view as a minimum. Views have been totally scrapped in GA4, with the only possible segmentation now coming in the form of web and app data streams. Yet again, the analysis hub must be configured by the user if you wish to simulate views in your reporting.

Pro – Consent mode and modelled conversions

I won’t go into too much detail on consent mode in this article, but more can be found here.

In essence, consent mode is Google’s privacy feature that helps to eliminate the use of cookies when users do not give explicit consent. With Universal Analytics, any data from non-consenting users is lost, but GA4 ingests this data in the form of anonymised and cookieless pings. This data is then used to model conversions, meaning you can report on all of your user interactions; not just interactions from consenting users.

In a post-GDPR world, we will need to rely on this kind of modelling, and Google’s solution will help to bridge the data gap caused by the increased focus on privacy in recent years.

Should I be using GA4 now?

July 2023 sounds like it might be a while away yet, but it’s crucial that you get GA4 running as soon as possible. There is talk of Universal Analytics properties being deleted six months after this date, so GA4 will be the only place to view historical data. If you wish to have year on year comparisons, you’ll need to get GA4 installed by this July.

GA4 brings some great new features to the table, but is missing some of the best parts of Universal Analytics. In my opinion, the best solution is to run both GA4 and UA in parallel (while you still can), and take the best parts from each. Create your audiences in GA4, make use of the BigQuery integration, but use UA for your day-to-day reporting and analysis. With Google’s recent announcement regarding Universal Analytics, now is definitely the time to start focussing on GA4, but I see no reason why you shouldn’t make the most of UA while it’s still available.

Final note

I’ve spent the last few months working with clients on Adobe Analytics. I can tell you that a lot of GA4’s functionality seems to be lifted directly from their playbook. Like Adobe Analytics, GA4 has the potential to be incredibly powerful, but can be a minefield to navigate. Whereas UA was built with the layman in mind, GA4 exists for the professional web analyst, data scientist, or business intelligence unit. If that isn’t you, perhaps you should get in touch!

The post The Case For and Against GA4 appeared first on Grapevine.

The value of Facebook shares can be seen as a good proxy for the state of online advertising in general. Whereas companies such as Google have varied income streams, Facebook ostensibly makes all of its money from advertising. 97.9% of Facebook’s global revenue in 2020 to be exact. As such, Meta’s share price and the online advertising market are intrinsically linked.

Many of us are wondering if Facebook’s recent misfortunes tell us something more serious about the state of online advertising, especially in the midst of international turmoil and a spiralling cost of living crisis.

Bleak quarterly reporting

February’s share price plunge came as a result of the release of Meta’s Q4 2021 financial reporting. Earnings per share were down to $3.67 for the quarter, from $3.88 the year before, despite quarterly revenue improving to $33.7bn.

Aside from earnings, the major concern was Facebook’s daily active users, which fell for the first time in its 18 year history. This led many to wonder if we had finally reached the peak, and ultimate decline of Facebook’s dominance as a social media platform. Competitors such as TikTok and Snap have done far better at cornering the market across the younger demographics, and allegations of corporate wrongdoing from whistleblower Frances Haugen have tarnished Facebook’s reputation globally.

Facebook’s Q1 2022 earnings per share slid further to $2.72. This time due to external factors, including the post-christmas slump, the war in Ukraine, oil and gas prices, and high inflation. Whilst the heat is off Facebook itself, thanks to the resurgence in its daily active users, there are several worrying macroeconomic trends in 2022 which may impact the whole advertising industry.

Apple’s privacy push

The road forward for Facebook is one with many challenges and opportunities. Year on year, ad impressions across their family of apps increased by 15%, but the average price per ad impression fell by 8%. CEO Mark Zuckerberg pointed to Apple’s privacy update generating a “meaningful headwind” for its targeted ads.

On a positive note, Facebook have shown they can still reach a wide user base with their advertising product – however, the lack of concrete targeting in a post iOS-14 world has made it harder than ever for advertisers to get their offering in front of the right people. Resultantly, users are engaging with on-platform advertising less and less, and Facebook has suffered monetarily.

Facebook keep it fresh with Reels

Another notable challenge is the emergence of TikTok, and the adoption of the short video format by competitors such as YouTube. Facebook have responded in kind with Reels, which are fast becoming the dominant medium on their apps. Reels now account for more than 20% of time spent on Instagram, with this figure growing month on month. Long and short-form videos account for 50% of the time that people spend on Facebook too.

Google knows all too well that video content is far harder to monetize. One only has to look at the consistently low CPMs for advertisers on YouTube to realise this. Facebook is aware, but will need to rely on video content to drive engagement, and keep TikTok from stealing even more market share. The challenge for Facebook will be to incorporate less intrusive ads into Reels without impacting user experience. If they succeed, advertisers will certainly benefit.

Navigating the cost of living crisis

Upward inflationary pressure will be the UK’s number one problem in 2022. The Bank of England have already confirmed they are duty bound to trigger a recession to curb inflation.

In real terms, this means people will have less disposable income to spend, and advertisers are bound to suffer.

Search advertising should be fairly well insulated – where there is a search, there is intent. Sadly, the same isn’t true for social media advertising. Anecdotal evidence suggests that advertisers are cutting budgets on platforms like Facebook, and focussing on bottom of the funnel activity such as remarketing. Facebook, and other social media platforms, will have to weather the storm, and will likely take a large hit to revenue in the coming months.

The outlook for 2022

The prospects for Facebook’s year ahead look mixed. On one hand, they have proved that the fall in user base may have been a temporary blip. Time on platform is also up thanks to the addictive nature of Reels. If they can work out a way to effectively monetize their new offering, they will be able to capitalise.

On the other hand, there are far too many market factors at play to make the road to redemption an easy one for Facebook. We don’t yet know how much the economy will slow in late 2022, but it’s clear that consumers’ purchasing ability will be diminished. Advertisers that stay on Facebook through this difficult time will need to make sure they are as efficient as possible.

Whilst the outlook for Facebook doesn’t look wholly positive, they have proven themselves to be a titan of the online advertising space, and we’re confident they will bounce back.

What should advertisers do?

Priority number one will be to set up the Facebook Conversions API, in order to bridge the gap in tracking caused by the Apple privacy features.

In the medium term, brands will need to focus on short-form video content, which looks like it could be the cornerstone of social media advertising moving forward. As for the inevitable slowdown in sales, it will be up to companies to decide if they need to cut advertising budgets, or keep themselves front and centre of the conversation by spending through the downturn.

The post What Facebook’s share price tells us about the future of the social media giant appeared first on Grapevine.

For example, brands are often put off making videos due to the cost of production and their social ads look like they’ve found an image online, added a bit of supporting text, and thought ‘that’ll do’.

We believe in the need for digital marketing agencies to be rooted in design and creativity and we also believe that high performing adverts can be clever, creative and good looking without costing the earth.

Here are five ad concepts that you could do now…

Age

When it comes to ‘good’ ads, its been said that they should be “personally identifiable and immediately relevant”. Tom.co.uk sell life insurance, a product typically bought by people over 40. In a recent set of ads, they mocked up a relatively bland image ad and signposted it with the age of the person they were targeting. This certainly ticks the relevancy box, and with the use of Facebook’s age targeting, means they can set them up easily. What’s more, they can get a gauge on the better converting age groups, and perhaps even manage the bid by the relative profit of users by age.

Location

Dynamic ad customizers are by no means a new feature in Google Ads. These allow you to dynamically change a headline and reference the searcher’s location (as defined by their IP address). It should come as no surprise to you that being local is a strong selling point – look at the thousands of local gin distilleries that have popped up in the last few years.

What’s also true is that appearing local can be just as powerful. Don’t believe me? Run local ads (such as in the example below) and watch your CTR% increase overnight.

Beyond the advert appearing local, it is also possible to dynamically change the headline on your landing page using Google’s ValueTrack parameters, and a script hosted on your website. This means you can sync your landing page with the headline on your advert, without needing to create 100s of unique location pages.

Video

As mentioned earlier, we find clients are not overly keen to create videos once they factor in the cost and estimated cost per lead/ROI. That said, we know that a video’s value extends beyond whether someone clicks on it, as its a useful way of driving brand awareness. What’s more, we think a good video should logically have a better chance of driving action than a single image or carousel.

Remember on YouTube, you only pay for skippable videos that viewers watch for 30 seconds or more. So, you don’t have to worry about paying for all those people who skip through your video as soon as they can. How many ads have you skipped, but remembered? That’s free branding.

One way to get round the (sometimes prohibitive) costs of videos is to film an FAQ video, like the one for Profit Accumulator above. This video is 3 minutes long and is a straightforward one-shot video of the business owner answering questions.

There’s no need for actors, as who is better placed to talk about their business than the owner, and the graphics are straightforward and professional. Is that a video you could make?

Carousel

Carousel ads are another old format used on most social platforms. Here’s an example of an ad similar to the Disney one above, but for a furniture brand. We liked this ad, as it’s a really simple way of getting existing customers to see your brand in a different way, without forgetting what you might have been known for. And lots of people agreed!

Funny

Ads should be memorable, and a sure-fire way of doing that is by going funny. What’s more, I don’t think you need to be a world-renowned comedian to come up with an amusing ad. Here’s a few that tickled me:

Before you go…

We know that coming up with ad concepts can be hard work. If you’re stuck on ideas, why not check out the Facebook ad library? Beyond that, we always encourage our team (and our clients) to answer the question: what’s your favourite advert? And why?!

If you’d like any help coming up with ad concepts or need an agency to manage your digital marketing. Or you just fancy a chat. Get in touch.

The post 5 Clever Ad Concepts (that you could do) appeared first on Grapevine.

However, with this announcement came the news that Performance Max campaigns were to replace Smart Shopping campaigns entirely by the end of July. With that in mind, it was important that we got up to speed with Performance Max before we were forced to!

The post Top Tips for Performance Max appeared first on Grapevine.