With 3.8 million apps available for Android users and 2 million apps in Apple's App Store, it can be tough for an app developer to stand out among the competition. But with Google's Universal App Campaigns (UAC), developers have an opportunity to market their mobile apps with targeting options based on audience demographics and behavior. It all happens automatically -- as long as you set up the campaigns correctly. In this post I take a look at how you can put machine learning to work for you, using the power of Google’s Universal App Campaigns. Campaign set up Getting started with a UAC is relatively easy. The three steps are to identify an audience, ensure conversion tracking is set up correctly, and relevant text, video, and images are available for the campaign. The two major actions for UACs are to find new users who will install the app or those who will perform an action inside the app, such as making an additional purchase. One the UAC is set-up, it is eligible to show on Search, Display, YouTube and the Play Store. The initial setup is straightforward. The advertiser only needs to provide four lines of text with images and with machine learning, Google decides which combination to show to a particular user. Goals When you consider goals for your UAC, the install action is an obvious one regardless of the app category. Targeting options includes people who are likely to install the app or who are likely to install it and perform in app action. It is up to the advertiser to determine what a valuable action looks like and ensure conversion tracking is set up before launching a campaign. In-app actions, or goals, or can be either success actions or proxy actions. With a success action, the app user makes a purchase inside the app, upgrades the service, or signs up for a paid subscription; something that generates revenue. Assuming success actions happen at least ten times a day with users, the system has enough data to identify and target the right audience for your UAC. If volume of success actions is low, there is not enough data for machine learning to make decisions. In that case, the advertiser can identify a proxy action which is a behavior that is likely to lead to success action. An example of this is someone who added payment information to upgrade service but did not follow through with upgrading. Or it could be tracking which of your users share incentives with their network. Advertisers need to think carefully about what a proxy action truly is. When it it is too early in the funnel, it includes people who are less likely to convert and not a good representation of those who will later perform a success action. If a mid funnel behavior is identified as a proxy action, rather the the top of the funnel, it may better represent people who are closer to converting so it is more likely to later result in a success action. Conversions Setting up and collecting conversion data is a crucial piece to success because these campaigns look at past searches, browsing behavior, and other apps used to determine who is most likely to convert. Before launching a UAC, ensure this conversion tracking is set up correctly or your will not be measuring goals that matter. For e-commerce sites, the primary conversion is clearly to drive revenue in the form of an in-app purchase or perhaps subscriptions. With luxury retail, it is especially important to have conversion recording correctly because of the multiple touch points. And Shopify users can use the Littledata reporting app to gain even more insight on the user journey through that platform. Measurement and optimization There are immediate metrics to monitor - app installs and in-app purchase - but there are also long term considerations such as the customer lifetime value (CLV), that should be part of your overall strategic marketing plan. A single user who makes a purchase provides direct revenue. If they refer someone to your app, that is considered indirect revenue. The first number is clear-cut revenue and easy to measure. The second is one that you determine based on your internal data, meaning what type of behavior and interaction with customers generally leads to a sale. The value of both of these actions contribute to the CLV. Lifetime is the length of time they interact with your app. If they install the app and use it to buy things over the course of a year, then stop, their CLV time period is one year. Once you have identified your CLV, use this value to set your target CPA and optimize it based on performance. Decide what you are willing to pay for a success action and what you will pay for a proxy action, knowing that number will likely change over time. As data comes in from your UAC, you can compare the lifetime value of your different customers through segments. Segments help you uncover those customers who purchase every couple months compared to those who only make an initial purchase. Those the make multiple purchases represent segments with a higher value. Drilling into data with segments allows you to see who gives you the best return for your investment. This level of detail helps you identify how much you paid in your UAC for to acquire each type of customer so you can adjust accordingly. Review what you paid initially for the type of users that you bring in and compare that to their lifetime value. Are you investing your budget in a UAC that brings in users that generate recurring revenue? When you bid strategically based on a lifetime value, you are not overly focused on short-term transactions. It is less expensive to keep a customer than to acquire a new one so you want to think in those terms. What next? Decide on UAC goals that make sense for the purpose of your app. What should users do in addition to downloading the app and what behaviors indicate they are getting close to a conversion? Gather assets - text, video, and image - that are enticing for users and ensure conversion tracking is setup properly. Without proper conversion tracking, you miss out on the data you need to determine success. Monitor performance of your campaigns, and if you run an ecommerce site, track a wealth of data with the Littledata app. Think about the CLV and optimize your campaigns to reach the right users rather than any users. Your bottom line is generating revenue so keep that in mind with every UAC. With careful planning and well managed campaigns, your app can stand out in a crowded marketplace.

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!

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.  

Conversion Optimisation is rarely a one-off job. You know that you should improve your landing page conversion rate, but where should you start? Whatever you decide to optimise to improve conversions, the process will take time and patience - whether you're optimising through design changes, A/B testing, or copywriting. In this post, I cover a range of landing page optimisation strategies, including CTAs and trust signals. There is always room for improvement on the website pages used for campaigns, especially when generic pages are used or visitors are sent to the home page. In an earlier post, we shared some best practices to reduce this friction. And there are multiple elements to test on a landing page, including the headline, images, use of testimonials, offers, and CTA. When optimizing for conversions, never test all those things at the same time because it will be hard to identify what worked, not to mention be very overwhelming. Below are suggestions of items to test that can have a big impact. 1) The right landing page headline Ideally, the headlines on our landing pages have a unique campaign proposition to get people to take the next step. When this is missing or unclear, there is no continuity from the traffic source that leads people to the page and results in the friction referenced above. Test variations on your campaign landing pages headlines as well as subject lines for emails and the titles for posts and articles. Different subject lines or headlines with the same content can have a big impact. 2) Trust signals Address customer concerns with trust signals, whether it is a product guarantee, testimonials, or a privacy policy. If you do not have brand recognition, you need these signals to make people comfortable with you. First trust signal: Use HTTPS Tech-savvy visitors may look for the https before your web address rather than http. As you can see below, the https indicates it is a secure connection, which protects sensitive information that may be submitted. Second trust signal: Justify form fields Give a reason for why you need information on website forms. If you do not have a good reason for requesting information, you should not make it required. It can turn away prospective customers who are not ready to provide that much information. 3) Remove words Look at copy critically. What can be removed from the page without changing the message? 4) Test alignment Test left aligned text and headlines compared to center aligned to see the different in performance. There are a lot of references on this topic but with testing, you can determine what works for your website. If the copy alignment makes it tough to read, visitors will not be around long enough to convert. 5) Use white space Create landing pages that are easy on the eyes with grouped content and white space. If you discovered words that can be removed - as mentioned above - this becomes easier to do as space is created from omitted content. 6) Group by color Group by color to show which things are related to each other on the page. The below dashboard shows items in green to indicate performance above the benchmark. Yellow indicates some room for improvement. There are different tools available to check the color contrast on your landing pages. 7) KISS (Keep It Simple, Stupid) Determining the offer on your landing page should never be difficult for site visitors. People should be able to see what it is within a couple seconds. If they have to read too much to figure out your offer or it is confusing, they may leave. 8) Reduce steps I received an email this week for a company that needs to reduce their steps. It asked me to click to confirm an appointment I made. When I clicked, it brought me to the homepage of the site with a prompt to log in with a username and password I did not remember. I did not look up my login info so I guess the appointment is not confirmed. (I will deal with it later!) Are there steps in your conversion process that can be eliminated? 9) Test CTAs Finally - and perhaps most importantly - you need a clear and measurable CTA. Ideally, your CTA is right next to the offer, rather than in a different section of the page. It can be a barrier if those elements are not close to each other. Note too if the CTA reflects where people are in the funnel. If I am being introduced to a product, I will respond to learn more. If I am ready to make a decision among several options, the CTA might say help me choose. Remember there are big actions and small actions. The macro action of help me choose puts money in the bank, but if that is my only option, I may not take any action since I am need to first learn more. Similarly, you can answer multiple web visitor questions, such as How much does it cost? and Where do I go to try your app?, with a CTA that says simply Start free trial. As you test the CTA on your landing page, and begin to collect performance data, you can learn how the response varies by segments. Search terms from ad campaigns or with site search can also indicate where people are in the funnel. Ok..but does the CTA really matter? Yes, the CTA really matters! I know small tests on a site can make a big difference, there is still the occasional example that blows my mind, like the Obama campaign donation button experiment results. It makes a case for why the choice of language in your CTA and segmenting your audience has an impact on conversions. In this example, the design features for the button were the same for all segments - a rectangular red button with white copy. But notice the difference in response rates based on the segment and copy on the button. Convinced that A/B testing for the small things matters? This test was done with variations in the CTA. The desired action was still a donation. Had they measured only the performance by CTA copy, they would have missed out on useful information about the segments. But had this experiment also included different colors, styles, and font, it would have been difficult to determine what resulted in a difference for each group. When optimizing for conversions, remember there are multiple areas to test but to never test everything at once. Make small incremental changes and continue to optimize based on performance. Littledata’s benchmarks are an easy way to keep track of where to improve, and there’s also a ton of additional content on the Littledata blog about conversions. We encourage you to look critically at areas to improve on your website pages, and then to take action!   Want to know more? Get in touch with Tina’s agency, 360 Internet Strategy, and follow her on LinkedIn.

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.

Buyer personas. User personas. PPC personas. Are these just marketing buzzwords? Do they mean months of planning before you can even begin your PPC campaigns? The answer to both questions is a straightforward no. 'User personas' don't require months of extra work to build, and they aren't just another marketing buzzword. If you follow my suggestions below, you can quickly create personas to help target and optimise your next PPC campaign. Start with brainstorming Brainstorming should come at the very beginning of your process. What do you already know about your audience? This can be old-school brainstorming with a pen and paper, or a more business-like approach with a whiteboard in your conference room. If you do this with a team, hand out some Post-it notes for jotting down ideas. The Post-it notes approach makes it very easy to move your notes around and begin grouping by identified themes. Quickly create simple personas The key here is simplicity.  There is great content out there on creating more complex personas, by using a resource such as Hubspot’s 100 Questions. For the simple approach, I look at three areas to kick things off. Describe the audience by their demographics: gender, location, age, parental status, income, etc.. Identify the biggest problems they want to solve. If you are unsure how to define this one, start with 'I want' or 'I need' to put yourself in the position of your audience. For example, as a marketer, my ongoing problems include automating mundane tasks and creating simple personas. Ask how your offering specifically solves the identified problems. When it comes to creating personas, Littledata can help by automatically building personas with existing Google Analytics data. With this information, create a very short narrative with the key descriptors and needs of each identified persona. Find the perfect image Do this after you finish the above steps. You do not want to start with image and then create a persona to look like that person. (There’s some great discussion on that on UX Mastery). One step I often recommend is to look at images of people in existing marketing materials to see if they represent the personas created from this exercise. Digital tools to help you create user personas After you do some brainstorming and jot down initial notes about personas, you can next turn to digital tools to help you. MakeMyPersona.com is aptly named because it helps you do just that.  It is a way to organize some of the thoughts that came up in the earlier steps. Those in the B2B market can try Up Close & Persona. It meets my criteria of simple and takes you through questions that help you think of appropriate messaging for your audience. However, some of the questions have only a few preset answers so I would not start this tool. It could box you into narrow thinking. Littledata’s buyer personas feature helps you identify the website visitors that are most likely to convert.  We know that Google Analytics does not do all the work for us, but there is a lot of data available for analysis. Compare these findings to what was uncovered during brainstorming. Develop your PPC campaign around the user persona Take your 'I want' and 'I need' statements and pull out some of those phrases as keywords. When it comes to choosing PPC keywords, stay away from your corporate lingo, and instead think about how your prospects talk about you. These keywords will help you match your message to each persona. Is your persona trendy with a sense of humor? Maybe you will get a little snarky with your messaging.  Is the need something serious, such as a health issue? Stay away from the snark and instead be really clear about your benefits. Create an offer that matches the persona. An intellectual, highly educated executive may take the time to download and read your white paper. A busy single parent with four young kids wants a solution. And wants it quickly. Segment personas by channel. I like Littledata's buyer personas because they let you see how to adjust your ad spend based on specific marketing channels beyond Paid Search. PPC is not the only place to reach your audience. You will - hopefully - have a multi-channel approach and need to understand Organic Search, Email, Referral, and Social in addition to PPC. Unless you have an unlimited marketing budget, you may not be able to reach every persona and on every channel. One consideration for your PPC spend is to focus on the longer tail or brand name keywords. This is definitely a smaller audience, but it will capture people further down the funnel who are more likely to buy. What to do next I hope that you find this simplified approach to developing personas useful in kicking of the next stage of your digital marketing! My goal is to provide steps for you to take action and not get bogged down by the prospect of developing personas before kicking off a campaign. You may want to refine this approach over time, but the important thing is to get started now. Even with the best planning, you may find some surprises in your campaigns after you get started which is why I always watch new campaigns closely, especially in those first few days. Monitor your performance by channels in Google Analytics and be prepared to adjust your ad spend. Your ROI will vary by offer and user persona, so focus on actionable analytics from this wealth of data to make the right decisions for your particular business.   Want to know more? Get in touch with Tina's agency, 360 Internet Strategy, and follow her on LinkedIn.