Category : Google Analytics
What's the real ROI on your Facebook Ads?
For the past decade Facebook’s revenue growth has been relentless, driven by a switch from TV advertising and online banners to a platform seen as more targetable and measurable. When it comes to Facebook Ads, marketers are drawn to messaging about a strong return on investment. But are you measuring that return correctly? Facebook has spent heavily on its own analytics over the last three years, with the aim of making you -- the marketer -- fully immersed in the Facebook platform…and perhaps also to gloss over one important fact about Facebook’s reporting on its own Ads: most companies spend money with Facebook 'acquiring' users who would have bought from them anyway. Could that be you? Here are a few ways to think about tracking Facebook Ads beyond simple clicks and impressions as reported by FB themselves. The scenario Imagine a shopper named Fiona, a customer for your online fashion retail store. Fiona has browsed through the newsfeed on her Facebook mobile app, and clicks on your ad. Let’s also imagine that your site -- like most -- spends only a portion of their budget with Facebook, and is using a mix of email, paid search, affiliates and social to promote the brand. The likelihood that Fiona has interacted with more than one campaign before she buys is high. Now Fiona buys a $100 shirt from your store, and in Facebook (assuming you have ecommerce tracking with Pixel set up) the sale is linked to the original ad spend. Facebook's view of ROI The return on investment in the above scenario, as calculated by Facebook, is deceptively simple: Right, brilliant! So clear and simple. Actually, not that brilliant. You see Fiona had previously clicked on a Google Shopping ad (which is itself powered by two platforms, Google AdWords and the Google Merchant Center) -- how she found your brand -- and after Facebook, she was influenced by a friend who mentioned the product on Twitter, then finally converted by an abandoned cart email. So in reality Fiona’s full list of interactions with your ecommerce site looks like this: Google Shopping ad > browsed products Facebook Ad > viewed product Twitter post > viewed same product Link in abandoned cart email > purchase So from a multi-channel perspective, how should we attribute the benefit from the Facebook Ad? How do we track the full customer journey and attribute it to sales in your store? With enough data you might look at the probability that a similar customer would have purchased without seeing that Facebook Ad in the mix. In fact, that’s what the data-driven model in Google Marketing Platform 360 does. But without that level of data crunching we can still agree that Facebook shouldn’t be credited with 100% of the sale. It wasn’t the way the customer found your brand, or the campaign which finally convinced them to buy. Under the most generous attribution model we would attribute a quarter of the sale. So now the calculation looks like this: It cost us $2 of ad spend to bring $1 of revenue -- we should kill the campaign. But there's a catch Hang on, says Facebook. You forgot about Mark. Mark also bought the same shirt at your store, and he viewed the same ad on his phone before going on to buy it on his work computer. You marked the source of that purchase as Direct -- but it was due to the same Facebook campaign. Well yes, Facebook does have an advantage there in using its wide net of signed-in customers to link ad engagement across multiple devices for the same user. But take a step back. Mark, like Fiona, might have interacted with other marketing channels on his phone. If we can’t track cross-device for these other channels (and with Google Marketing Platform we cannot), then we should not give Facebook an unfair advantage in the attribution. So, back to multi-channel attribution from a single device. This is the best you have to work with right now, so how do you get a simple view of the Return on Advertising Spend, the real ROI on your ads? Our solution At Littledata we believe that Google Analytics is the best multi-channel attribution tool out there. All it misses is an integration with Facebook Ads to pull the ad spend by campaign, and some help to set up the campaign tagging (UTM parameters) to see which campaign in Facebook brought the user to your site. And we believe in smart automation. Shhhh...in the past few weeks we've quietly released a Facebook Ads connection, which audits your Facebook campaign tagging and pulls ad cost daily into Google Analytics. It's a seamless way to pull Facebook Ads data into your overall ecommerce tracking, something that would otherwise be a headache for marketers and developers. The integration checks Facebook Ads for accurate tagging and automatically pulls ad cost data into GA. The new integration will normally only be available in higher-tier plans, but we're currently offering it as an open beta for ALL USERS, including Basic plans! For early access, just activate the Faceb|ook Ads connection from your Littledata dashboard. It's that easy! (Not a subscriber yet? Sign up for a free trial on any plan today.) We believe in a world of equal marketing attribution. Facebook may be big, but they’re not the only platform in town, and any traffic they're sending your way should be analysed in context. Connecting your Facebook Ads account takes just a few minutes, and once the data has collected you’ll be able to activate reports to show the same kind of ROI calculation we did above. Will you join us on the journey to better data?
Intro to the Littledata app (VIDEO)
How does the Littledata app work? It's magic! Or at least it feels that way. This new video gives a quick overview of how it all fits together. Our ecommerce analytics app is the only one on the planet to both fix your tracking and automate reporting. Our customers see dramatic growth, from higher add-to-cart rates to better return on paid search. But what happens first, and what happens next? If you're an ecommerce marketer using Google Analytics, Littledata will make your job a whole lot easier. The process breaks down to four core steps, which you can repeat as often as you'd like. First you connect your analytics account, marketing channels like Google AdWords and Facebook Ads, and website data from tools like Shopify, ReCharge and CartHook. (And yes, we'll help you comply with GDPR). Then you use the Littledata app to audit your analytics setup and fix your tracking. Shopify stores can fix tracking automatically -- other sites get clear recommendations on what to do. If your goals include higher marketing ROI and increased conversions, the next step is to automate reporting with report packs and a smart dashboard, available directly in the app. And then it's time to optimise revenue with industry benchmarks, enhanced reporting and buyer personas, all built automatically. Sign up today for a free audit of your analytics setup, or book a demo to learn more. A complete picture of your ecommerce business is just around the corner!
How auditing Google Analytics can save you money
When is the last time you audited your Google Analytics account? If the answer is 'never', I understand, but you could be wasting a ton of cash - not to mention potential revenue. It's easy to put off an analytics audit as a 'someday' project considering the multitude of other tasks you need to accomplish each day. But did you know that auditing your Google Analytics account can save you money and add a big bump to online revenue, even with sites that are not ecommerce? Whether people spend money directly on your site, or your site is primarily for lead generation, you spend money to get those site visitors through your marketing channels. When you view a channel like AdWords, there is a clear financial cost since you pay for clicks on your ads. With organic traffic, such as from Facebook fans, you spend time crafting posts and measuring performance, so the cost is time. With an investment of any resource, whether time or money, you need to evaluate what works - and what does not - then revisit the strategy for each of your marketing channels. In this post, I’ll walk you through some of the automated audit checks in Littledata and take a look at what they mean for your online business. If your analytics audit doesn't ask the following questions, you're probably wasting money. Is your AdWords account linked to Google Analytics? If you run AdWords campaigns, linking AdWords and Analytics should be at the top of your to-do list. If AdWords and Analytics are not linked, you cannot compare your AdWords campaign performance to your other channels. Although you can still see how AdWords performs within the AdWords interface, this comparison among channels is important so you can adjust channel spend accordingly. If you discover that AdWords is not delivering the business you expected compared to other marketing channels, you may want to pause campaigns and reevaluate your PPC strategy. Are you tracking website conversions? There should be several conversion goals set up on your website because they represent visitor behavior that ultimately drives revenue. The above example shows a warning for a lead generation website. Although it is possible that no one contacted the site owner or scheduled an appointment in 30 days as indicated in the error, it does seem unlikely. With this warning, the site owner knows to check how goals are set up in Google Analytics to ensure they track behavior accurately. Or, if there really was no engagement in 30 days, it is a red flag to examine the strategy of all marketing channels! Although the solution to this warning will be different based on the individual site, this is an important problem to be aware of and setting up a goals in Google Analytics, such as for by destination, is straightforward. You can also get creative with your goals and use an ecommerce approach even for non-ecommerce websites. Do you use campaign tags with social media and email campaigns? This is an easy one to overlook when different marketing departments operate in silos and is a common issue because people do not know to tag their campaigns. Tagging is how you identify your custom social media and email campaigns in Google Analytics. For example, if you do not tag your paid and organic posts in Facebook, Google Analytics will lump them together and simply report on Facebook traffic in Google Analytics. In addition to distinguishing between paid and organic, you should also segment by the types of Facebook campaigns. If you discover poor performance with Facebook ads in Google Analytics, but do great with promoted posts in the Facebook newsfeed, you can stop investing money in ads at least for the short term, and focus more on promoted posts. Are you recording customer refunds in GA? Refunds happen and are important to track because they impact overall revenue for an ecommerce business. Every business owner, both online and offline, has dealt with a refund which is the nature of running a business. And this rate is generally fairly high. The return rate for brick-and-mortar stores is around 9% and closer to 20% for online stores, so less than 1% in the above audit seems suspicious. It is quite possible the refund rate is missing from this client’s Google Analytics account. Why does this matter? Let’s assume the return rate for your online store is not terrible - maybe 15% on average. However, once you track returns, you see one product line has a 25% return rate. That is a rate that will hurt your bottom line compared to other products. Once you discover the problem, you can temporarily remove that product from your inventory while you drill into data - and talk to your customer support team - to understand why that product is returned more than others, which is a cost savings. Are you capturing checkout steps? Most checkouts on websites have several steps which can be seen in Enhanced Ecommerce reports in Google Analytics. Shoppers add an item to their cart, perhaps log-in to an existing account or create a new one, add shopping information, payment etc. In the ideal world, every shopper goes through every step to ultimately make a purchase, but in the real world, that is rare. Last year alone, there was an estimated $4 trillion worth of merchandise abandoned in online shopping carts. Reasons for this vary, but include unanticipated extra costs, forced account creation, and complicated checkouts. By capturing the checkout steps, you can see where people drop out and optimize that experience on your website. You can also benchmark checkout completion rates see how your site compares to others. Are you capturing product list views? If you aren't tracking product list views correctly, your biggest cash cow might be sleeping right under your nose and you wouldn't even know it! Which products are the biggest money makers for you? If a particular product line brings in a lot of buyers, you want to make sure it is prominent on your website so you do not leave money on the table. Product list views enable you to see the most viewed categories, the biggest engagement, and the largest amount of revenue. If a profitable product list is not frequently viewed, you can incorporate it in some paid campaigns to get more visibility. The good news An audit is not only about what needs fixing on your website, but also can show you what is working well. After you run an audit, you will see the items that are set up correctly so give yourself a pat on the back for those - and know that you can trust reporting based on that data. Either way, remember to run an analytics audit regularly. Once a month is a good rule. I have seen cases where a website was updated and the analytics code was broken, but no one noticed. Other times, there may be a major change, such as to the customer checkout, so the original steps in your existing goal no longer work. Or an entirely new marketing channel was added, but with missing or inconsistent tagging. It is worth the time investment to ensure you have accurate Google Analytics data since it impacts influences your decisions as a business owner and your bottom line. Littledata's automated Google Analytics audit is especially useful for ecommerce sites, from online retailers to membership sites looking for donations. It gives a clear list of audit check results, with action plans for fixing your tracking. And Shopify stores can automatically fix tracking to capture all marketing channels and ensure that data in Google Analytics matches Shopify sessions and transactions (not to mention the data in your actual bank account!), even when using special checkouts like ReCharge and CartHook. When you're missing out on the revenue you should already have, an audit is the first step in understanding where it's falling away, or where you're over-spending. Run an audit. Make a list. Fix your tracking. Grow your revenue. Sometimes it really is that simple!
CartHook integration for tracking one-page checkouts and upsells
We're excited to announce that Littledata now fully integrates with CartHook. The integration provides automatic tracking for sales from CartHook's one-page checkout and connects that data to marketing channels and shopper behaviour. Littledata -- CartHook integration is the easiest way to get accurate data and smart reporting to improve sales and marketing ROI. All you need is a Shopify store with CartHook Checkout installed (even for just one product) and a Google Analytics account! What is CartHook? CartHook makes it easy for Shopify stores to add customisable one-page checkouts and post purchase one-click upsells. Their intuitive funnel builder lets any store customise the checkout process to increase conversions and decrease abandonment. Features include: Customisable one-page checkout One-click post-purchase upsells, including for subscription products (works great with our ReCharge integration) Product Funnels allow you to send traffic to a pre-loaded checkout page from any landing page Native Shopify integration means no custom coding required! How it works Integrating CartHook with Littledata ensures that all sales activity is tracking correctly in Google Analytics. Littledata weaves together your Shopify and CartHook data and connects it with your marketing channels and campaigns. Why spend developer time on custom scripts and events when you can just activate the integration in a couple of minutes? Benefits of CartHook integration: Sales tracking - Get automatic tracking for sales from CartHook, seamlessly synced with sales made via standard Shopify checkout Marketing attribution - Connect marketing channels and campaigns with shopping cart activity and buyer behaviour Optimisation - Scale the smart way with Littledata's industry-leading optimisation tools, including a personalised dashboard, report packs, benchmarks and buyer personas It's all about accurate data. Littledata's script runs in the background, pulling from CartHook, Shopify, and any other source you've connected to your analytics. If you're an advanced Google Analytics user, you can dig into the improved data collection directly in GA. Read more about why CartHook customers should use Littledata. Setup guide For the Littledata -- CartHook integration to work, you need to have both apps installed for your Shopify store, then connect them by activating the integration. Install CartHook and Littledata Follow these steps to activate the integration Yes, it's that easy! Shopify Plus If you run a larger Shopify store on Shopify Plus, we're here to help you scale. Both Littledata and CartHook offer enterprise plans that include custom setup and a dedicated account manager. Larger stores looking for an enterprise plan or managed services are encouraged to sign up directly and then contact us for a free consultation. If you're a digital agency with multiple customers on Shopify using CartHook, even better! Check out our agency partner program for Shopify experts.
The World Cup guide to marketing attribution
It’s World Cup fever here at Littledata. Although two of the nationalities in our global team didn’t get through the qualifiers (US & Romania) we still have England and Russia to support in the next round. And I think the World Cup is a perfect time to explain how marketing attribution works through the medium of football. In football (or what our NYC office calls 'soccer'), scoring a goal is a team effort. Strikers put the ball in the net, but you need an incisive midfield pass to cut through the opposition, and a good move starts from the back row. ‘Route one’ goals scored from a direct punt up the pitch are rare; usually teams hit the goal from a string of passes to open up the opportunity. So imagine each touch of the ball is a marketing campaign on your site, and the goal is a visitor purchasing. You have to string a series of marketing ‘touches’ together to get the visitor in the back of the net. For most ecommerce sites it is 3 to 6 touches, but it may be more for high value items. Now imagine that each player is a different channel. The move may start with a good distribution from the Display Ads defender, then a little cut back from nimble Instagram in the middle. Facebook Ads does the running up the wing, but passes it back to Instagram for another pass out to the other wing for Email. Email takes a couple of touches and then crosses the ball inside for AdWords to score a goal – which spins if off the opposing defender (Direct). GOAL!!! In this neat marketing-football move all the players contribute, but who gets credit for the goal? Well that depends on the attribution model you are using. Marketing attribution as a series of football passes Last interaction This is a simplest model, but less informative for the marketing team. In this model the opposing defender Direct gets all the credit – even though he knew nothing about the end goal! Last non-direct click This is the attribution model used by Google Analytics (and other tools) by default. In this model, we attribute all of the goal to the last campaign which wasn’t a Direct (or session with unknown source). In the move above this is AdWords, who was the last marketing player to touch the ball. But AdWords is a greedy little striker, so do we want him to take all the credit for this team goal? First interaction You may be most interested in the campaign that first brought visitors to your website. In this model, Display ads would take all the credit as the first touch. Display often performs best when measured as first interaction (or first click), but then as a ‘defender’ it is unlikely to put the ball in the net on its own – you need striker campaigns as well. Time decay This model shares the goal between the different marketing players. It may seem weird that a player can have a fraction of a goal, but it makes it easy to sum up performance across lots of goals. The player who was closest to the goal gets the highest share, and then it decays as we go back in time from the goal. So AdWords would get 0.4, Email 0.5 (for the 2 touches before) and Instagram gets 0.1. Data-driven attribution This is a model available to Google Analytics 360 customers only. What the Data-driven model does is run through thousands of different goals scored and look at the contribution of each player to the move. So if the team was equally likely to score a goal without Facebook Ads run down the wing it will give Facebook less credit for the goal. By contrast, if very few goals get scored without that pass from Instagram in the midfield then Instagram gets more credit for the goal. This should be the fairest way to attribute campaigns, but the limitation is it only considers the last 4 touches before the goal. You may have marketing moves which are longer than 4 touches. Position based Finally you can define your own attribution weighting in Position Based model, based on which position the campaign was in before the goal. For example, you may want to give some weight to the first interaction and some to the last, but little to the campaigns in between. Still confused? Maybe you need a Littledata analytics expert to help build a suitable model for you. Or the advice of our automated coach known as the analytics audit. After all, every strategy could use a good audit to make sure it's complete and up-to-date. So go enjoy the football, and every time someone talks of that ‘great assist’ from the winger, think of how you can better track all the uncredited marketing campaigns helping convert customers on your site.
Increase ecommerce conversion rates with segments in Google Analytics
Are you generating enough site traffic? Are there enough visitors each month that engage with your content and spend time on your site? Those are good things, but the important question is how you are doing with conversions, as that is where the magic happens! For many businesses, there will be slumps where conversions are not where you need them to be and increasing conversions is tougher than bringing in visitors. The reasons for not converting are many, which could include a poorly designed landing page or frustration with a slow page load time. Fortunately, the technical aspects of your site are somewhat clear cut and influence all users to the site. Either it loads quickly or it does not. It responds to mobile devices or does not. But there are principles that are about the groups visitors to a site. What do they search for and can you provide it? How are they different from each other? How are they similar? In short, you need smart segmentation if you want to continue to increase conversions. Here's a quick guide to using segments in Google Analytics. Segments vs personas In this post, we will build on some of the work you have hopefully done to create personas and highlight the value of segments when optimizing for conversions. Personas help you be empathetic to your customers. Visualizing a 35-year old professional female makes it easier to create the right message for her rather than general messages to all women. This is not about stereotypes. Personas help you hypothesize about similarities in how people behave. So how is that different from segments? There is confusion with segments versus personas and you want establish a definition for your team so you all work from the same framework. In the simplest terms, you segment your audience with existing data and create campaigns based on personas. Start with your segments. With Google Analytics, you can use segmentation to group people by identifying criteria such as location. Think of segments as the somewhat objective view of your audience based on raw data. (There is still some subjectivity when deciding the makeup of segments). Personas are very subjective - based more how a person thinks or feels. Get to know your audience with Google Analytics Google Analytics provides a lot of data that helps us understand our segments if we go beyond basic metrics, such as pageviews. Below are a few ways to learn more about your segments with the goal of increasing conversions and adding depth to your personas. Pages per Session: This is a basic metric in Google Analytics but you can go beyond scenarios, such as users visiting two pages compared to those visiting seven pages. Look at which pages they visited. Did they visit the intro offerings (probably a newcomer) or the help section (probably an existing customer)? Did they read the entire section about a topic (more methodical) or buy on the first visit (maybe more impulsive)? Note these are assumptions about motivations but you can develop hypotheses based on behavior. Content Grouping: Content grouping categorizes your site content based on rules created in the Admin section of your Google Analytics account. Once you have these rules, you can view content groups for different scenarios, such as where people are the journey, how they flow through content, how they came into your site (traffic source), and how much time they spent on there. For sites with thousands of pages, this makes it more manageable than viewing individual pages. You can analyze conversions on the categories of your site rather than a specific page. Cohort Analysis: Found in the Audience section of Google Analytics, this is used to examine the behavior and performance of groups of users related by common attributes. It allows you to view a group of visitors based on a shared acquisition date. If you have a drip campaign scheduled for May, you may want a Cohort Date Range of May 1 to May 7 to target people who first visited the site during that time period. You can learn if people who visited on a specific day were more inclined to visit again than other members of that group. User Login: Custom Variables can be fired when users login. That provides additional data for more advanced segments by identifying the behavior of different customer types. Site visitors self-segment when they log into the site to take an action. With Custom Variables, you can see how behavior is different for those who log-in versus those who do not. Bounce Rate: We all get hung up on this metric. People see a site bounce rate of 78% and begin to panic but you need to drill in to see if that matters. Do existing customers and regular visitors bounce from a blog post? That is expected. However, if new people regular bounce from the site, look at the landing pages. There could be a message mismatch with the source that sent them to a particular page. Affinity Segments: Use affinity and in-market segments in Google Analytics to help define your personas. They are broad classifications about users which may be helpful when layered on top of other characteristics. For example, you may discover segments that prefer one content grouping over another. Collect metrics that matter When there is a difference in the conversion rate and user journey among segments, it indicates your identified segments truly represent distinct types of users. Read that again because whether your segments make sense determines whether your data is any good. With the right segments, you can determine which groups to cultivate or which ones to not pursue with limited resources. For example, if one segmented group regularly buys add-ons for product, that might justify allocating more advertising dollars. With target segments identified, you can also look at which marketing effort attracted them to your site. Some of this is obvious. If users in their 30s never respond to a CTA on your site from Facebook, you may not want to pay for ads on that channel or even post to it regularly. So yes, we all care about who converts compared to those who do not. But remember there are stages leading up to a conversion and this Facebook audience could still have a role, so watch where in the process people drop off. And hopefully by now you realize that non-converters are more than just non-converters. View this by segment too to identity what non-converters may have in comment. As data comes in, additional segmenting can be done by on locations, time of conversion, brand search terms versus early stages searches. But do not collect data for the sake of collecting data. Although it is easy to do with the abundance of data available in Google Analytics, it does not guarantee a return for your efforts. Want to know more? Get in touch with Tina’s agency, 360 Internet Strategy, and follow her on LinkedIn.
Google Analytics Data Retention policy - which reports does it limit?
From 25th May 2018 Google allowed you to automatically wipe user-level data from the reporting from before a cut-off date, to better comply with GDPR. We made the change for Littledata's account to wipe user-level data after 26 months, and this is what we found when reporting before February 2016. Reports you can still view before the user data removal Audience metrics Pageviews ✓ Sessions ✓ Users X Bounce rate ✓ Audience dimensions Demographics X OS / Browser X Location X User Type X Behaviour Pageviews ✓ Custom events X
How to implement a successful mobile marketing strategy
Mobile as a marketing strategy isn’t a new idea to anyone, but the landscape is changing quickly. Back in 2015, Google told us it would be expanding its use of mobile-friendliness as a ranking signal. More recently, in early 2018, they stated that page speed will be a ranking factor for mobile searches middle of this year. As consumers change their behavior on mobile devices, this greatly impacts our strategy as marketers. We now need to be visible on all devices, all the time. What do all these changes mean for marketers? Whether you're a solo AdWords consultant or a member of a digital agency, it's essential to stay on top of consumer trends in a way that is measurable and repeatable. In this post I break down how to develop a data-driven mobile marketing strategy that can easily scale with your online business. Mobile search has changed As consumers, we are research-obsessed. We want to know everything we can about an ecommerce product or service so we can make informed decisions. And as more of us search for seemingly minor things and do so on a small device, advertisers have the opportunity to be present in those micro moments. With an increase of searches on mobile devices (and with mobile searches already having bypassed desktop searches several years ago) we need to be present across the entire consumer experience, making the customer experience a business priority regardless of our brand or business size by providing a seamless experience on every device. Analyzing data with a last-click attribution model misses some of these mobile moments. Assumptions have changed along with search behaviors. In September 2015, Google shared that “near me” or “nearby” searches on Google had grown 2X in the previous year, but the use of that phrase has since declined. People still want results that are near them, but the assumption of today’s searchers is that Google knows the location of the searchers and where to find what was searched because people are using their devices throughout the day. Increase of use for “open now” and “tonight" and “today” travel-related terms indicate people are seeking information on their device. What this means for brands Does your strategy consider these trends and adjust to changes in consumer behavior? A mobile experience leads to a brand impression. People expect a consistent experience every time they interact with a brand. If your site does not deliver and does not deliver quickly, they will quickly leave. Regardless of which channel they used to get to your site, the mobile experience must be as seamless as the desktop experience. What this means for Google AdWords As mobile use continues to increase and consumer behavior changes, we need to better align our PPC efforts and use an attribution model that addresses all steps of the journey. With AdWords, we can align our marketing strategy to mobile use with mobile search ads, mobile display ads and app ads on mobile devices. Each option offers slightly different features. Text ads can display on any device. The primary difference with ads on mobile vs desktop is more ads per page on a desktop and only a couple on a mobile device. Because the first couple ads take up most of the screen on a smartphone, advertisers need to be in the first or second position because that is all that will display. Impatient searchers will not scroll down on their device to your ad in position four. On the Display Network, you can be more creative with ads, adding images and videos to the mix. Although image sizes that work on desktop computers will also work on mobile devices, aim for a smaller size of 320 x 50 when possible, keeping the layout of smaller screen sizes in mind. The third option for mobile ads are appearing on mobile apps, which are part of the Display Network. App promotion ads have a goal of driving downloads. Campaigns with only app promotion ads are eligible for phones and tablets; they are not on desktop computers. Bid adjustments With your AdWords campaigns, set bids on mobile devices that are aligned with your goals. As mentioned above, many will not scroll down the search results page on a smartphone to view ads so may want to increase these bids. This is also important for branding goals; you need to be at the top to be seen. When determining mobile bids based on ROI, identify ROI for desktop versus tablets and devices. That way, your adjustment is based specifically on the mobile value of conversions. Keywords In any AdWords campaign, the key to success is selecting the correct keywords. But you can go a step further and use the keyword tool to also see mobile trends for your selected keyword over the previous year. Use these findings to inform your bidding strategy. A subjective approach is to view your keywords in the eyes of your users. Are the keywords in your campaigns ones that you would type into your mobile device? Although more people use voice recognition to search, there are still those who type in their request. Since typing on a small screen results in typos, you want broad match keywords in your campaign when targeting mobile users. Make sure these keywords include action-oriented terms. Some people may surf their device out of boredom while standing in line, but many search to find information to make a decision. You can capture these early clicks with an attribution model other than last-click. Mobile URLs Google provides an option of using mobile URLs in ads to customize the mobile experience, but if the mobile URL is the same as the Final URL in AdWords, adding it does not impact mobile performance. This is designed for people who have different pages for mobile users. AMP pages An open source initiative, Accelerated Mobile Pages (AMP) solve the issue around slow landing pages to make them faster for mobile. Business that have used them find a much quicker loading time and a more engaging experience. You can also use the AMP version of your website in this option for final URL Bid strategy Take advantage of machine learning with a Smart Bidding strategy in your AdWords campaigns. It considers the multiple signals around device type and browser for auction-time changes, offering more targeting than we could do manually as an AdWords account manager with simple bid adjustments. Monitor device performance with this strategy and prioritize mobile traffic if it does particularly well on devices. Attribution models In all AdWords campaigns, regardless of device, many advertisers use the last-click attribution model, which is not ideal for any campaign, including those targeting mobile. It gives all the credit for a conversion to the last touchpoint - the last click - which misses out on how other interactions influenced the decision to convert. If you have enough data in your account, utilize the Data-Driven Attribution Model. If it is not available to you, consider one of the other options besides last-click attribution. The right reporting for mobile marketing Before you target mobile users with advertising, check first that your site performs well on mobile devices if you do not plan to have a mobile specific URL. Start with a quick test for mobile speed to see if you are at risk of losing traffic. Next do a quick SEO check of your site which is based on Google’s guidelines, which is also relevant to paid traffic. For all your campaigns, not just AdWords, you need to consider metrics such as sessions by device type for general site behavior and conversions once a campaign is running for a while. To minimize manual work for reporting and analysis, use a Littledata report pack which pulls in data from Google Analytics to offer automated reporting on customer touch points, providing data you need without the manual labor. And remember your mobile users are on the go, so any advertising needs to cater to them in the moment! Want to know more? Get in touch with Tina's agency, 360 Internet Strategy, and follow her on LinkedIn.
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