There are literally millions of people who wish they could quit their day jobs. With an uncertain economy, nasty bosses, a dreadful commute and salaries that allow you to only live from paycheck to paycheck… the idea of making a living online is a dream held by many.
Paid Social Media Jobs is an online program that promises that you can make money online easily if you purchased their program. A story about a lady, Annie Jones, is used to inspire confidence in the training and the earning potential of this course.
We decided to take a closer look at Paid Social Media Jobs and this is what we found out…
The Good Points:
1) With the thousands of scams and hyped up opportunities online, Paid Social Media Jobs is one of the more trustworthy ones. There are people who are making good money as social media managers. This course will give you a good foundation to get started and make some money online.
Of course, to get to 4 or 5 figures a month, you’ll need to work on your skills and look beyond this course. Nevertheless, it’s a good start.
2) The instructions are laid out in an easy to understand manner that will make it a breeze to follow. People who are not savvy with computers and the internet will be able to understand the process and follow it in a step-by-step way.
3) The program is an online bestseller. To some extent this is reassuring.
4) There are a variety of methods to choose from. So, there’s something for everyone here.
5) This product is backed by a 100% money-back guarantee. You can test it out for 60 days and if you do not make any money with Paid Social Media Jobs, you can get a refund and recoup your investment.
6) The methods shown are scalable. Once you understand how it all works, and you gain confidence in completing and delivering jobs, there’s nothing stopping you from trying out other freelancing platforms to increase your income.
The Bad Points:
1) The sales copy has a lot of hype and can make people skeptical. Over and above that, the earning potential is exaggerated. While the methods shown do work, you’ll not make as much as the sales copy claims.
To get to that level, you’ll need to work on your business for quite a while. This is not a ‘get rich quick’ program like the sales page wants you to think it is. Nevertheless, if you want a simple and straightforward way to make a couple of hundred or a few thousand a month, this course can help you.
2) You can only purchase this product online.
Should You Get It?
If you’re looking to supplement your income with a couple of hundred every month, this is a good way to start. Freelancing is a proven business model and Paid Social Media Jobs will show you what to do.
It’s relatively easy to follow and has very low startup costs. After all, you can get a free account with most social media sites. From there, it’s just a matter of following the instructions in this program.
Most people will benefit from just a couple of hundred dollars extra. It could take care of your utilities bill or a car payment or cover gas money… and so much more. Once you get better at it, you could start outsourcing or arbitraging and making a couple of thousand each month.
Of course, that’s in the future when you have experience. But it all starts now. Paid Social Media Jobs will give you that stepping stone towards diversifying and increasing your income. Definitely worth trying.
Posted by scott.taft We’ve been talking a lot about search intent this week, and if you’ve been following along, you’re likely already aware of how “search intent” is essential for a robust SEO strategy. If, however, you’ve ever laboured for hours classifying keywords by topic and search intent, only to end up with a ton of data you don’t really know what to do with, then this post is for you. I’m going to share how to take all that sweet keyword data you’ve categorized, put it into a Power BI dashboard, and start slicing and dicing to uncover a ton insights — faster than you ever could before. Building your keyword list Every great search analysis starts with keyword research and this one is no different. I’m not going to go into excruciating detail about how to build your keyword list. However, I will mention a few of my favorite tools that I’m sure most of you are using already: Search Query Report — What better place to look first than the search terms already driving clicks and (hopefully) conversions to your site. Answer The Public — Great for pulling a ton of suggested terms, questions and phrases related to a single search term. InfiniteSuggest — Like Answer The Public, but faster and allows you to build based on a continuous list of seed keywords. MergeWords — Quickly expand your keywords by adding modifiers upon modifiers. Grep Words — A suite of keyword tools for expanding, pulling search volume and more. Please note that these tools are a great way to scale your keyword collecting but each will come with the need to comb through and clean your data to ensure all keywords are at least somewhat relevant to your business and audience. Once I have an initial keyword list built, I’ll upload it to STAT and let it run for a couple days to get an initial data pull. This allows me to pull the ‘People Also Ask’ and ‘Related Searches’ reports in STAT to further build out my keyword list. All in all, I’m aiming to get to at least 5,000 keywords, but the more the merrier. For the purposes of this blog post I have about 19,000 keywords I collected for a client in the window treatments space. Categorizing your keywords by topic Bucketing keywords into categories is an age-old challenge for most digital marketers but it’s a critical step in understanding the distribution of your data. One of the best ways to segment your keywords is by shared words. If you’re short on AI and machine learning capabilities, look no further than a trusty Ngram analyzer. I love to use this Ngram Tool from guidetodatamining.com — it ain’t much to look at, but it’s fast and trustworthy. After dropping my 19,000 keywords into the tool and analyzing by unigram (or 1-word phrases), I manually select categories that fit with my client’s business and audience. I also make sure the unigram accounts for a decent amount of keywords (e.g. I wouldn’t pick a unigram that has a count of only 2 keywords). Using this data, I then create a Category Mapping table and map a unigram, or “trigger word”, to a Category like the following: You’ll notice that for “curtain” and “drapes” I mapped both to the Curtains category. For my client’s business, they treat these as the same product, and doing this allows me to account for variations in keywords but ultimately group them how I want for this analysis. Using this method, I create a Trigger Word-Category mapping based on my entire dataset. It’s possible that not every keyword will fall into a category and that’s okay — it likely means that keyword is not relevant or significant enough to be accounted for. Creating a keyword intent map Similar to identifying common topics by which to group your keywords, I’m going to follow a similar process but with the goal of grouping keywords by intent modifier. Search intent is the end goal of a person using a search engine. Digital marketers can leverage these terms and modifiers to infer what types of results or actions a consumer is aiming for. For example, if a person searches for “white blinds near me”, it is safe to infer that this person is looking to buy white blinds as they are looking for a physical location that sells them. In this case I would classify “near me” as a “Transactional” modifier. If, however, the person searched “living room blinds ideas” I would infer their intent is to see images or read blog posts on the topic of living room blinds. I might classify this search term as being at the “Inspirational” stage, where a person is still deciding what products they might be interested and, therefore, isn’t quite ready to buy yet. There is a lot of research on some generally accepted intent modifiers in search and I don’t intent to reinvent the wheel. This handy guide (originally published in STAT) provides a good review of intent modifiers you can start with. I followed the same process as building out categories to build out my intent mapping and the result is a table of intent triggers and their corresponding Intent stage. Intro to Power BI There are tons of resources on how to get started with the free tool Power BI, one of which is from own founder Will Reynold’s video series on using Power BI for Digital Marketing . This is a great place to start if you’re new to the tool and its capabilities. Note: it’s not about the tool necessarily (although Power BI is a super powerful one). It’s more about being able to look at all of this data in one place and pull insights from it at speeds which Excel just won’t give you. If you’re still skeptical of trying a new tool like Power BI at the end of this post, I urge you to get the free download from Microsoft and give it a try. Setting up your data in Power BI Power BI’s power comes from linking multiple datasets together based on common “keys.” Think back to your Microsoft Access days and this should all start to sound familiar. Step 1: Upload your data sources First, open Power BI and you’ll see a button called “Get Data” in the top ribbon. Click that and then select the data format you want to upload. All of my data for this analysis is in CSV format so I will select the Text/CSV option for all of my data sources. You have to follow these steps for each data source. Click “Load” for each data source. Step 2: Clean your data In the Power BI ribbon menu, click the button called “Edit Queries.” This will open the Query Editor where we will make all of our data transformations. The main things you’ll want to do in the Query Editor are the following: Make sure all data formats make sense (e.g. keywords are formatted as text, numbers are formatted as decimals or whole numbers). Rename columns as needed. Create a domain column in your Top 20 report based on the URL column. Close and apply your changes by hitting the “Edit Queries” button, as seen above. Step 3: Create relationships between data sources On the left side of Power BI is a vertical bar with icons for different views. Click the third one to see your relationships view. In this view, we are going to connect all data sources to our ‘Keywords Bridge’ table by clicking and dragging a line from the field ‘Keyword’ in each table and to ‘Keyword’ in the ‘Keywords Bridge’ table (note that for the PPC Data, I have connected ‘Search Term’ as this is the PPC equivalent of a keyword, as we’re using here). The last thing we need to do for our relationships is double-click on each line to ensure the following options are selected for each so that our dashboard works properly: The cardinality is Many to 1 The relationship is “active” The cross filter direction is set to “both” We are now ready to start building our Intent Dashboard and analyzing our data. Building the search intent dashboard In this section I’ll walk you through each visual in the Search Intent Dashboard (as seen below): Top domains by count of keywords Visual type: Stacked Bar Chart visual Axis: I’ve nested URL under Domain so I can drill down to see this same breakdown by URL for a specific Domain Value: Distinct count of keywords Legend: Result Types Filter: Top 10 filter on Domains by count of distinct keywords Keyword breakdown by result type Visual type: Donut chart Legend: Result Types Value: Count of distinct keywords, shown as Percent of grand total Metric Cards Sum of Distinct MSV Because the Top 20 report shows each keyword 20 times, we need to create a calculated measure in Power BI to only sum MSV for the unique list of keywords. Use this formula for that calculated measure: Sum Distinct MSV = SUMX(DISTINCT(‘Table'[Keywords]), FIRSTNONBLANK(‘Table'[MSV], 0)) Keywords This is just a distinct count of keywords Slicer: PPC Conversions Visual type: Slicer Drop your PPC Conversions field into a slicer and set the format to “Between” to get this nifty slider visual. Tables Visual type: Table or Matrix (a matrix allows for drilling down similar to a pivot table in Excel) Values: Here I have Category or Intent Stage and then the distinct count of keywords. Pulling insights from your search intent dashboard This dashboard is now a Swiss Army knife of data that allows you to slice and dice to your heart’s content. Below are a couple examples of how I use this dashboard to pull out opportunities and insights for my clients. Where are competitors winning? With this data we can quickly see who the top competing domains are, but what’s more valuable is seeing who the competitors are for a particular intent stage and category. I start by filtering to the “Informational” stage, since it represents the most keywords in our dataset. I also filter to the top category for this intent stage which is “Blinds”. Looking at my Keyword Count card, I can now see that I’m looking at a subset of 641 keywords. Note: To filter multiple visuals in Power BI, you need to press and hold the “Ctrl” button each time you click a new visual to maintain all the filters you clicked previously. The top competing subdomain here is videos.blinds.com with visibility in the top 20 for over 250 keywords, most of which are for video results. I hit ctrl+click on the Video results portion of videos.blinds.com to update the keywords table to only keywords where videos.blinds.com is ranking in the top 20 with a video result. From all this I can now say that videos.blinds.com is ranking in the top 20 positions for about 30 percent of keywords that fall into the “Blinds” category and the “Informational” intent stage. I can also see that most of the keywords here start with “how to”, which tells me that most likely people searching for blinds in an informational stage are looking for how to instructions and that video may be a desired content format. Where should I focus my time? Whether you’re in-house or at an agency, time is always a hit commodity. You can use this dashboard to quickly identify opportunities that you should be prioritizing first — opportunities that can guarantee you’ll deliver bottom-line results. To find these bottom-line results, we’re going to filter our data using the PPC conversions slicer so that our data only includes keywords that have converted at least once in our PPC campaigns. Once I do that, I can see I’m working with a pretty limited set of keywords that have been bucketed into intent stages, but I can continue by drilling into the “Transactional” intent stage because I want to target queries that are linked to a possible purchase. Note: Not every keyword will fall into an intent stage if it doesn’t meet the criteria we set. These keywords will still appear in the data, but this is the reason why your total keyword count might not always match the total keyword count in the intent stages or category tables. From there I want to focus on those “Transactional” keywords that are triggering answer boxes to make sure I have good visibility, since they are converting for me on PPC. To do that, I filter to only show keywords triggering answer boxes. Based on these filters I can look at my keyword table and see most (if not all) of the keywords are “installation” keywords and I don’t see my client’s domain in the top list of competitors. This is now an area of focus for me to start driving organic conversions. Wrap up I’ve only just scratched the surface — there’s tons that can can be done with this data inside a tool like Power BI. Having a solid data set of keywords and visuals that I can revisit repeatedly for a client and continuously pull out opportunities to help fuel our strategy is, for me, invaluable. I can work efficiently without having to go back to keyword tools whenever I need an idea. Hopefully you find this makes building an intent-based strategy more efficient and sound for your business or clients. Sign up for The Moz Top 10 , a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!
21-Year-Old Marketing Genius Nabeel Ahmad Shares His Top 3 Marketing Tips for 2019. Posted on by admin Nabeel Ahmad is the founder and CEO of Vertabyte, a full-service digital agency that partners with clients to drive their business outcomes. After having worked with many businesses to handcraft the best marketing campaigns, Nabeel has established himself as one of the top marketing experts of the 21st century. He is also the founder of The Influencer Factory, which is a PR agency that specializes in strategic media placements. Over the years, Nabeel has partnered with many influencers, entrepreneurs, startups and established companies, and has successfully gotten them featured on major publications like Forbes, Entrepreneur, Huffington Post, Inc Magazine, and more. I recently had a chance to meet Nabeel Ahmad, and here are 3 marketing tips he shared with me that can help businesses dominate the marketing landscape in the 21st century. Harness the power of Influencer Marketing. An influencer is a person who has a large number of followers on social media, and people love to follow his/her lifestyle. Influencers can be actors, singers, YouTubers, or anyone who has a large following on social media. In this era of social media, influencer marketing has become a strong force in business and marketing. Many top brands have been paying influencers to promote their content to their followers, which leads to a lot of sales and increase in revenue. In 2019, it is absolutely essential that businesses utilize the power of influencer marketing in order to beat their competition.
Produce engaging content. As we all know content is king. Whether it’s on your own website or on social media, it’s your content that will engage your followers. You may be able to attract a large crowd for yourself by using social media marketing, but only strong content will make them inclined to keep following you. In the 21st century, there is too much content on social media, and attention spans are decreasing. In order to stand out from the crowd, your content must be unique and interesting. People want to see and read interesting stories, or things that benefit them. If you are unable to provide that, people will just divert their attention to others who are able to provide them what they want. The goal is not to simply put content in front of people and hope they respond to it, but rather to encourage them to share and engage with it. Content — whether it’s an article on an outlet or a video on social media — opens the door for two-way communication, which is crucial for building trust and letting customers know that you appreciate their business. Therefore, it’s essential to make your content interesting and easy to read. This will have a huge impact on your business in the long run.
Don’t ignore video marketing In 2019, videos have the highest engagement rate out of all types of content on social media. That’s the case on all social media, not just YouTube. If you want to increase your following then try to upload engaging videos on your social media pages. The video can be in various forms like vlogs, interviews, webinars, presentations, tutorials, product reviews, testimonials or animations.The best strategy for video marketing is to start with competitor analysis. Research your competitors, see what type of video content they are producing, and find out what type of videos are getting the most engagement. This will help you craft the best video marketing strategy, and will save you money that would have been wasted on marketing videos that aren’t that engaging. It was a pleasure discussing marketing with one of the top experts in this industry. Nabeel Ahmad can be reached on Facebook @nabeelahmad101, or on Instagram @nabeelahmad19
Mobile Commerce: More Than Responsive Design. Tuesday, February 19, 2019
More Than Responsive Design. It is no surprise that mobile commerce is an important trend in retail . In fact, eMarketer predicts that by 2021, the mobile commerce market will represent 72.9% of the ecommerce market worldwide. Just go into any store and watch how many shoppers check their mobile phone at some point. They might use their mobile device to do some quick research, do some price shopping, or check something completely unrelated. Consumers are addicted to smartphones. Today’s shopping experience includes mobile. As mobile users, we are consummate social media, news feeds, podcasts, messaging, gaming, and mobile app junkies. Yet when it comes to mobile commerce – are we doing enough in retail? Mobile Commerce in Retail Button’s 2019 mobile commerce report reviews the mobile behavior of consumers over the holiday shopping season. This research specifically compared in-app mobile purchasing against mobile web purchasing. In other words, are shoppers more likely to buy from a mobile responsive site, or from a mobile-optimized app? It turns out that consumers using mobile-optimized apps made 108% more purchases in-app. This compared to consumers doing their online shopping on a mobile responsive site (mobile web). Now, let’s compare to what retailers are actually offering in the market, from the Omni-2000 research . From the 2000+ retailers reviewed internationally, 75.9% have mobile responsive – mobile commerce. This is definitely laudable. Yet, the research found that only 8.3% of retailers currently offer mobile commerce optimized sites or mobile applications. If we know that consumers make 108% more purchases on mobile-optimized sites (apps), then we have a gap. Many, if not most good electronic commerce platforms (ECP) provide responsive site capabilities. This is great but can lure a retailer into thinking that their mobile strategy is fully covered. But, given Button’s research results, mobile-optimized sites or apps provide the user experience that promotes buying. Mobile Commerce by Country By country, retailers in Germany/Austria and the UK were most likely to offer mobile responsive sites. UK tops the chart at 83.4%, with Germany/Austria close behind at 83.0%. For mobile-optimized sites, or mobile apps, retailers in France excel. In France, 12.3% of retailers offer mobile commerce on mobile-optimized sites or apps. See the chart directly taken from the Omni-2000 research, for a summary of each country. [Source: OrderDynamics’ Omni-2000 Global Research] Optimization = More Commerce [Source: Button 2019 Mobile Commerce Report] Not only did consumers using mobile apps spend more, but they also converted at a higher rate. Conversion rates are 14% higher on mobile apps than on mobile. Button also shows that apps have a 177% higher revenue per tap, compared to mobile websites. Further, apps also showed a 108% higher number of purchase orders compared to mobile commerce on responsive sites. Power User = SuperConsumer? Like the discovery of the Click and Collect Superconsumer , Button uncovered power users. This groups placed 130% more (double+) mobile commerce orders (6.2) compared to average users. Although power users are only 8% of all shoppers, they accounted for 22% of sales during the holiday shopping cycle. Retailers can easily fall in love with this group, as they made more than 6 shopping trips. During that time, they also converted at twice the rate of the average user. M-Trend It does not take much convincing to see that mobile commerce is a strong retail trend. Accenture (2016) noted that “48% of all shoppers said they found it easier to make purchases using their mobile devices compared to 42% last year.” M-commerce is becoming easier to use. It enables users to buy goods and transact anywhere they are at. Used as mobile wallets, it becomes a simple purchase transaction for consumers. Finally, once a relationship is established, it even allows retailers to use push notification to interact with customers. Clearly, it is a trend no retailer wants to miss. Is an App All I Need? It is clear that retailers need to focus on mobile-optimized sites or apps as part of their mobile commerce strategy. However, retailers must also ensure this integrates into the overall omnichannel strategy. Mobile commerce needs to be integrated into the distributed order management (DOM / OMS) technology. This is where systems like OrderDynamics’ DOM, truly shines. Unified into the broader omnichannel system, mobile commerce transactions become part of the seamless retail solution. This promotes a single and easy user experience. Integrated well, mobile becomes another fully functional sales channel. Done well, the shopper can access all information, like a location’s available inventory. Orders can be placed for delivery, in-store pickup, or reserved. Shoppers can then use the retailer’s payment gateway to pay with credit cards, debit, Apple pay, loyalty points, gift cards, or any other combination. But, the important part here is to ensure the mobile app is not an orphan. Coupled with the order management system, it becomes a powerful retail sales channel. Not Just Shoppers By extension, mobile commerce is also part of the store. POS (point of sale) systems like that of PCMS, are increasingly using mobile technology. The beauty is that systems like that of PCMS are designed to integrate with third-party speciality systems, and unify with order management technology like that of OrderDynamics’. Not only let in-store staff use mobile devices to see what is in stock, and where, but it also lets them use the endless aisle concept to ‘save the sale’. Mobile commerce here lets associates scan, pay and get on their way, faster. It no longer tethers the cash counter. Now even wireless handheld devices are evolving to the next step. Wearable tech now allows authorizations and price-overrides from a distance. Store managers and supervisors don’t have to be recalled to the front desk for each of these transactions. If this seems trivial, try running from the front to the back of a big box store twenty times consecutively. Even a smaller store can make the customer experience faster and more positive with quick authorizations, not needing the supervisor to come to the cash desk each time. All told, the in-store buy and sell process is just easier. <span data-mce-type=”bookmark” style=”display: inline-block; width: 0px; overflow: hidden; line-height: 0;” class=”mce_SELRES_start”>ï»¿</span> How About In-Store? Deloitte’s 2018 research surmises the mobile commerce experience as a part of the omnichannel buying journey. Deloitte states, “consumer demand for a mobile-friendly experience will grow as the smartphone becomes more pervasive in our lives. But this does not just mean mobile-friendly websites for retailers, it means integrating the mobile experience into every element of the customer journey.” Mobile commerce cannot be a standalone sales channel. It must be integrated into the order management ecosystem and omnichannel retail strategy. This means ecommerce, mobile and in-store will all provide the same customer experience. Full inventory information available on all platforms. And, all must be able to transact orders, when the customer wants to buy. Retailers have done a good job of adopting responsive design. But, more effort has to go into creating mobile-optimized sites and apps for mobile commerce. Early adopters here are already reaping the benefits of higher conversion and increased sales. Whether you call it mobile selling, mobile commerce, M-commerce or any other title, this an emerging retail channel that is gaining momentum. It is now clear, optimization is not an option. It is a core necessity. Equally, integrating your mobile commerce solutions into the omnichannel ecosystem will quickly become table stakes in retail. Author: Charles Dimov is VP of Marketing at OrderDynamics. Charles has 23 years experience in Marketing, Sales and Management across various IT and Technology businesses. Previous roles include Chief of Staff, Director Product Marketing, and Director Sales. Charles has held roles in brand name firms like IBM, Ericsson, HP, ADP, and OrderDynamics.
Made in NYC Stock quotes by finanzen.net Instagram is already running out of room for ads, and that’s a threat to Facebook as it looks for new avenues to keep revenue growing Feb. 18, 2019, 7:21 AM Facebook CEO Mark Zuckerberg Facebook A few years ago, Instagram was red-hot for advertisers, with its 500 million-strong young audience. But like the Facebook feed, the Instagram feed is coming close to reaching its saturation point for ads, even though it runs two-thirds fewer ads than Facebook does. As the feed gets more crowded and expensive, Facebook is trying to shift advertisers towards its Stories ads on Instagram, Facebook and Messenger. Advertisers have been slow to shift, though, because the Stories ads require their own creative and don’t reach as many people as feed ads do. In 2016, Instagram’s ad business was booming and Facebook was reaping the rewards of its $1 billion acquisition of the mobile app four years earlier. Advertising was still new to Instagram, but the app, with its 500 million young users, represented a significant amount of shiny, new inventory to advertisers, particularly as they shifted spend from desktop to mobile. As Instagram copied features from rival Snapchat — including its now popular Stories feature where users post ephemeral, vertical content — marketers pumped spending into Facebook’s sibling app that was seen as critical to Facebook’s growth. Now Facebook has started warning investors that the company’s hockey-stick growth may be waning as both the Instagram and Facebook feeds reach a saturation point with ads. “When we look into 2019, we do expect to see a deceleration of revenue growth throughout the year,” said David Wehner, Facebook’s chief financial officer, during the company’s fourth-quarter earnings call. “While we have opportunities to grow impressions on Facebook and Instagram, that’s less so in feed, where we already have healthy ad loads.” Read more: Facebook has a plan to solve advertisers’ lingering measurement concerns — but Google is already a step ahead To be clear, Facebook is a money-printing machine. It grew ad revenue 37% year-over-year to $56 billion and added one million advertisers in 2018. But growing demand from Facebook’s seven million advertisers has made it more expensive to advertise in the feeds. According to data from Marin Software that tracked Facebook ad spend during the fourth-quarter, Instagram feed ads cost more than both Facebook’s feed and Stories ads. The data suggests that Instagram ad prices are going up. Per Marin Software, the average cost-per-click for Instagram feed ads was 85 cents, versus 53 cents for Instagram Stories ads and 18 cents for Facebook feed ads. That’s led Facebook to try to diversify its revenue sources by betting big on Stories . Two million of its seven million advertisers have run Stories ads. But advertisers have been slow to make the switch to Stories because they’re challenged to make the vertical-oriented creative required of Stories. The Stories audience isn’t as big as the feeds’, and they say Stories ads don’t perform as well as feed ads. In an average campaign where advertisers spend $100,000 on Facebook, $95,000 still goes to feed ads with the remaining $5,000 going to Stories, Rosenblatt Securities analyst Mark Zgutowicz said. “Initially I’ve seen ads where they’re using the same creative that they were using in feed. That doesn’t work and it really needs to be customized,” said Meghan Myszkowski, VP of social activation at Essence North America. “Facebook ads in feed are the mainstay. They are always a very strong performer when you find the right target and the right creative.” Associated Press Instagram isn’t the full-blown ad juggernaut of Facebook The Instagram feed is reaching its saturation point even though it’s only sold ads earnestly for four years compared to Facebook’s 12 years. That’s because as Facebook has turned on its ad spigot in recent years, it’s been cautious about flooding Instagram with ads. During a 10-minute scroll through a feed, users see two to three ads on Instagram compared to up to 10 ads on Facebook, according to Zgutowicz. “They wanted to keep Instagram as pure as possible,” he said. “It has a different user base that is generally speaking younger and less tolerant for ads, whereas the more mature adults on [Facebook’s] feed have grown up with ads.” Facebook doesn’t break out Instagram’s ad revenue, but Zgutowicz estimated that Instagram makes up about 15 percent of Facebook’s revenue, roughly even with 2017 when Instagram represented about 14% of Facebook’s mobile revenue, according to estimates from research firm eMarketer. Zgutowicz said he doesn’t expect the percentage to grow meaningfully over the next few years. “Until we get to pricing double where we are today in Stories ads, it doesn’t press the needle much in Instagram’s ad revenue contribution,” he said. Juliette Leavey, associate director of digital strategy at Deutsch, said that the many security and data concerns facing Facebook over the past year will lead it to pull back ad inventory in Instagram this year. “Instagram has less inventory because they’re trying to protect their platform,” she said. “We’re seeing in 2019 that they’re going to be very protective.” The lines between the apps is blurring Over time, it may matter less if advertisers get crowded out of Instagram. The distinctions between the apps is blurring for advertisers as they increasingly rely on Facebook’s own technology that gives Facebook control over where ads appear. Facebook has been testing an “automatic placements” tool where brands upload their ads and Facebook determines the best place and time to run them. The tool can also convert creative into Stories and determine if it’s better to run an ad in the Facebook or Instagram feeds. Agencies say that the tool makes their Facebook buys more efficient, so they’re less concerned about the audience differences between Facebook and Instagram. “In a lot of cases, we’re not necessarily buying one platform specifically over the other — we’re buying against an audience or performance KPI,” said iCrossing’s chief media officer Jeff Ratner. “It makes it one inventory pool as opposed to a couple of different inventory pools.” To that point, advertisers are increasingly trying to tie together all of Facebook’s apps in their ad buys, and Stories is the company’s first ad product to run across Facebook, Instagram, and Messenger. Facebook has also said it plans to roll out similar ads in WhatsApp later this year. “When you approach Facebook now, it’s not just thinking of feed, it’s the entire Facebook ecosystem,” said Essence North America’s Myszkowski. “You kind of have to look at it as the full package.”
The number of advertising networks, features and management tools available to PPC marketers is continuously expanding and making PPC management more complex than ever. Leaning into the power of automation is essential for modern day PPC specialists to deliver strategic input and guidance needed to deliver continuous improvement for clients. Looking at marketing budget trends, spend on martech is increasing compared to spend on in-house teams (labor), PPC and agencies. Those marketers able to demonstrate that they can harness automation to achieve similar benefits to martech platforms will retain more of the budget than those who fail to adapt over the year ahead. Source: Emarketer- CMO Budget Spending, November 2018 Automating as many manual processes as possible as well as utilising the power of machine learning to manage campaigns within set parameters can provide marketers with the time required to keep on top of the evermore complex PPC environment and free up time for tasks that machines can’t do (yet) such as building forward-thinking strategies for clients across relevant networks. Let’s now take a look at how automation can help with some otherwise labor-intensive tasks associated with managing ads on Google or Bing. Automating bid management PPC marketers still relying on a fully manual bid management process are now few and far between. Manually managing bids is hugely time-intensive and inefficient considering the number of options available to automate bid management currently accessible on even the smallest budgets. Some bid management methods are slightly more advanced than others. Entry level bid management can be achieved by using automated bid management options available on Google ads , indeed even automated rules can work for smaller accounts. It’s no secret that Google is keen for advertisers to use their automated bidding strategies in campaigns. Their smart bidding features use advanced machine learning to amend bids based on a wide range of real-time signals including device, location, time of day, remarketing list, language and operating system. The following smart bidding strategies are available within Google Ads to advertisers who reach minimum conversion requirements within 30 days: Target CPA Bidding : Sets bids to help get as many conversions as possible at a set target cost per acquisition (CPA) Target ROAS : Target more conversion value or revenue based on a target return-on-ad-spend (ROAS) Enhanced CPC : Looks for ad auctions that are more likely to lead to conversions, and then raises your max CPC bid automatically We have been testing Google’s smart bidding strategies on our clients over the past quarter and comparing results to scripts we’ve built to automate bids based on target ROAS / CPA goals. The results we’ve seen from using Google’s smart bidding strategies have been more impressive than the bespoke Google scripts we’ve relied on in the past to manage bids across accounts. Source: Hallam client data Q4 2018 – Google smart bidding comparison By increasing the number of data points used as part of their bidding strategies, there is now a much deeper data-set for advertisers to use as part of Google’s out of the box automated bidding strategies which will benefit smaller advertisers in particular who may not previously have been able to harness this data. Layering auto bidding with relevant scripts Layering smart bidding with management scripts that factor in client specific data such as seasonality, stock levels and other factors was unsurprisingly the most successful tactic overall from the trial above. One example of how scripts can help automate bid management alongside auto bidding strategies is taking into account client-specific data such as product level profit margin. Within the data feed for Google Shopping, custom labels can be used to identify the profitability of products. For example, labels such as 0-10 percent, 10-20 percent, 20-30 percent, etc., are passed through to Google Shopping to split products by profitability. Bids can then be automatically increased or decreased hourly to align with the profitability of a product compared to the average profitability across all products. For example, if a profit had half the margin as average, then the bid would be halved and if another product had triple, then the bid would be tripled. Automating error checking Identifying anomalies that may indicate performance issues within an account is a core responsibility for a PPC account manager. However, it’s unlikely that a human can trawl through larger accounts at the required rate to stay on top of all issues before they start to do serious damage to performance. Existing Google scripts are available to assist with broad error checks across accounts, like Google’s Account Anomaly Detector . This script will automatically scan an account every hour and prompt an email whenever account metrics vary more than a set percentage from expectations. Taking this a level further, Google scripts can be used to check for specific issues within accounts. As an example, we have set up a script for our e-commerce clients to output the number of approved products on Google merchant center. If there is a “significant” shift in the number of approved products an email is sent out as an alert to the account manager in question prompting them to take action sooner than they otherwise would have done. This script catches things like feeds expiring, a client randomly deciding to take a bunch of products out of the feed as well as the standard disapproval messages sent out by default by Google. Automating ad copy For larger accounts ad copy creation will be a time-consuming process. However, there are some ways this can be automated to save yourself time. Dynamically generate ads based on your website content – DSA Google dynamic search ads (DSAs) enable advertisers to automatically target and generate ads based on their website content. A good way of expanding accounts but crucially DSA’s don’t have the same level of control or the level of targeting options as keyword-targeted campaigns. Create ads based on data feeds using Google Scripts Creating ads for larger accounts using Google Scripts is recommended over DSAs. However, you will need to have an up to date product data feed and in-depth knowledge of Google sheets to use this method. You can find out more about how to auto-create ads using Google scripts on our post on the topic here . Automating PPC reporting There are a variety of free options available to PPC marketers for report automation. One of the most customizable is through Google sheets using a Google Analytics add-on. Using the Google Analytics add-on for sheets, you’ll be able to pull in selected metrics and dimensions and customize the visualization of your data using Google sheets charting functionality. A couple of other handy (free!) methods of automating your PPC reporting include: Setting up and automating custom reports in Google Analytics Setting up PPC dashboards in Data Studio If you’re still manually recording performance statistics from your PPC accounts then I’d strongly recommend giving one of the options above a try to save yourself countless hours of time each day/week/month building out Excel sheets – a little time upfront to customise and automate a dashboard will save you lots of time over the long term. Conclusion This post outlines just a few ways in which you can harness the power of automation and machine learning to both deliver improved results and more efficiently manage PPC accounts. Automation can provide us with analysis and management assistance at a scale that humans aren’t capable of providing in the same timescale, saving us time to focus on the bigger picture for clients. One worthwhile action after reading would be to assess where your biggest “ time vampires” are in your daily PPC management routine, and identify processes which could technically be automated to save you time to add value to your accounts. Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here .