One huge targeting mistake and how to avoid it: Understand the context beyond few keywords

Contextual advertising is not new, when I first started writing about targeting advertising the technology was new, the concept was new and few bold marketers were trying and learning from their mistake while helping others teach on how not to make this mistakes.

A post by Kevin Hillstrom, Highly Targeted Digital Ads That, Well, Just Read The Article., tells me that we have yet to learn from the mistakes that have been made since the early years of online ad targeting.

I remember when we are first dabbling withdisplay ad targeting and retargeting back in early 2000s, one of the things we were trying to solve for is to understand the full context of the content you were reading.  We saw many marketers making the mistake of not understanding the negative context of the content and wasting their ad dollars on wrong content. For example we saw an ad targeted (I believe it was served by Google) on a page talking about plane crash that showed an ad for carry-on luggage. When you are reading such a tragedy, last thing you want to see is an ad about plane travel. Technology and best practices have come a long way since then but the same mistakes keep happening.

Here are two things you can today to make sure you do not make the same mistake as VW dealer (or their agency) made:

1. Filter ad placement on negative context: If you are going to show an ad about your brand then understand the whole context and then filter out any content that has negative context related your brand. For example the whole context of that video was about negative to VW because of recent emission scandal. You as a marketer need to know that a lot of recent content (video, articles, blog post etc.) are going to be about this scandal, so keeping this context in mind, create a list of negative keyword list e.g. emission, scandal, problem etc. Now filter out the ad targeting on the content which contain “Volkswagen” and these negative keywords because if you place your ads on such content it is likely not going be very effective. Stop wasting your dollars by targeting the wrong context.
2. Show Ad to counter the negativity around your brand – If there is a message that you have in response to the negative press then use this opportunity to put your message in front of the customer and prospects.

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Are Your Insights Interesting or Actionable?

“What is the business objective and who is the audience?” this is the question you should always ask before developing data insights.  This will help you figure out if you need to focus on Interesting or actionable insights. Yes, actionable insights are also interesting but not the way Media thinks. Media hypes Interesting Insights, insights that might not be actionable and valuable to the business. Your business stakeholders might prefer actionable insights over interesting. I said might because some business stakeholders (sometimes) will prefer Interesting even though that can’t do much with it, it just sounds good in their presentation.

Let’s look at example of Interesting insights that gets coverage in Media.

For example, here is except from The Weather Channel’s Secret: Less Weather, More Clickbait

“We can tell you that on a January morning in Miami, if a set of weather conditions occurs, people will buy a certain brand of raspberry,” he says. Not just any fruit. Raspberries. When advertisers ask for an explanation—why raspberries?—Somaya can’t always provide a clear answer. “A lot of times we have to tell them to just trust us.” Other times, he finds correlations that make perfect sense. “There’s a particular dew point percentage that makes everyone in Dallas rush out and buy bug spray,” he says. “We couldn’t figure out why, then we realized that insects’ eggs hatch at that dew point.” Basically, everyone in Dallas was getting bitten at once.

Great, very interesting but as a business what will you do with it? If you are a grocery store in Miami then either you have raspberry in stock or not. If you have it then great, you don’t need those insights. If not then you can’t just go order your distributors to get you the Raspberries when those set of conditions happens.  Ordering takes time and so does shipping, by the time you get those raspberries in your store it is already too late.

Similarly in the second case, you can’t just go ahead and start stocking bug spray when the dew point hits a certain point. Either you have them in stock and you will sell them or you don’t have them then by them time you get that shipment, dew point has already changed. Let’s assume that you are able to use advertising (mobile/online/social/TV) when the right conditions (dew point and other conditions) happen.  But, by the time customer gets the message those conditions are most likely already over, leaving your advertising worthless. But Media does not care about that, all they care about is more readership which comes when there is something interesting.  In a nutshell, such insights are developed for Media, if that’s your goal then sure go ahead and generate and publicize them.

Actionable insights on the other hand might not be as interesting to the outside world but as they are to your business. These insights will certainly provide the value to your business.  If you tell your stakeholders that customers buy notebooks in two weeks leading up to school opens (back to school) and buy calculators a week after school opens, then that is an insight you can use to drive more sales. You can plan your inventory and advertising based on school start dates. Media likely won’t talk about such insights but it is actionable and interesting (for the business).

So when coming up with insights always keep in mind the objective and your audience. Both Interesting and Actionable have their place but don’t confuse one for the other.

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CMOs: Three Major Roadblocks to Insights

Data is the raw material for developing insights. If the complete data is not available to insights team then you can’t expect the insights to be very valuable. Insights teams will make the best out of what they have available but you will get far better insights if you spend little time with them to understand what they need and help them with these for major roadblocks.

1. Data Sources and Collection – Insights team has identified the data sources required for them to provide great insights, the data is all there either available internally or externally. The big challenges comes when the data teams actually start to figure out how the data will be collected. For internal data sources the organizational barriers are the biggest ones that prevent one team for getting access to the data that other team owns. Your team will need your help in navigating those barriers and help the free flow of the data. If external data sources are on their list then your help will be needed to provide appropriate funding and legal clearance needed to get those data pieces.
2. Data Storage – Storage per GB/TB is cheap and will continue to be cheaper but with that the amount of data will continue to go up (see the graph below) All in all, you will end up either spending a lot of money or will need to clear out the data repository to keep cost in check. Clearing the data means data gaps will emerge causing the gaps in Insights. For example, if all your data team can store is six months’ worth of data then you will be missing out on yearly trends, If all they can store for 1 year then you will be missing out on multi-year trends etc. Your team will need your support in ensuring that you have appropriate budgets approved to ensure that your team can store the required amount for their analysis.

Source: http://www.eweek.com/c/a/Data-Storage/Storage-Management-10-Business-Factors-That-Will-Impact-IT-Pros-in-2012-181588

3. Data Access – Having all the data collected and stored is half the battle, other half is making sure that the data is accessible by the insights team. Majority of the time the data will be stored in the cloud, Hadoop etc but is not easily available to the analysts who will need it for their analysis. In order to make any sense of the data, the insights team needs to have easy access to the data, not just in little chunks but to the whole set. You analysts might not be well versed with database technologies to make proper connection. They need an easy way to either connect their analysis tool e.g. Tableau, Excel etc. to the data sources so they can pull the required data to conduct analysis. They will need your help in pushing the other teams to make data accessible to them.

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4 KPIs for Measuring Email List Growth

Email list growth is the foundation of email marketing program. Unless you keep care in protecting and growing that list you will end up non functional email marketing program. Recently, I wrote a post on 23 Metrics for Email Marketing Metrics that you should know about, in this post I am taking 3 metrics from that list and adding one more to call out the 4 KPIs (Key Performance Indicators) to measure the email list growth.  Here are the four KPIs:

1. Email Complaint Rate/Spam Complaint Rate – SPAM complaints can kill your marketing program. This KPIs allows you to see if SPAM complains are becoming an issues, you goal should be to minimize this KPI. Spam complaint rate is measures as the percentage of your email recipients who marked your emails as Spam. Looking at this number campaign by campaign and then aggregated over month will show you if you are annoying your subscribers to a point where they consider your email as spam. This number is readily available in most of the ESP.
2. Subscribe Rate – This KPI measure the effectiveness of your marketing/content in driving new email subscribers.  Your goal should be to increase this KPI. Subscribe rate is expressed as a percentage and is calculated as New Subscribers divided by visitors who are not already in your list. Most of the Web Analytics tools will provide you this number by tracking the completion of emails subscription page as a goal/conversion. These tools use the total goal conversions divided by total visitors on the site during the specified period to calculate the conversion rate (Subscribe Rate). The default conversion rate calculation by web analytics tool will also count anybody who has already subscribed to your list thus inflating the denominator. In most cases the default calculation will suffice but if you do want to get accurate numbers then you will have to setup your web analytics tool to not count people who are already subscribed.
3. Unsubscribe Rate – Is the percentage of your emails recipients (subscribers) who chose to unsubscribe from your future mailings. Unsubscribe Rate is calculated as number of unsubscribes divided by email delivered and is expressed as a percentage. It measures the effectiveness of your email marketing strategy and the quality/relevance of your email marketing. If this number continues to rise, you have a problem that should be immediately fixed. The fixes range from adjusting the email frequency to increasing the relevance of the message.
4. List Growth Rate – This is ultimately the one metric that everything else boils down to. If you have to only show one metric on your dashboard or optimize for one metrics then use this one as it is calculated using the other three that I have listed above.  This KPI measures how fast your email list is growing, it is the net results of new subscribers minus the unsubscribes (including hard bounces) and email/spam complaints. It is calculated as, Growth (new subscribers ) – Loss(unsubscribes + email complaints) divided by total list size of your email list. Your email marketing program depends on List Growth so watch this number closely and take actions to actively grow your email list.

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Here are few more email marketing posts that you will like:

1. 23 Email Marketing Metrics That You Should Know
   This post lists all the email marketing metrics that you will ever need.
2. One costly email mistake that you can easily fix
   Growing email list is a hard job. All you Growth hacking goes down the drain when you make a simple mistakes that costs you subscribers that you just gained. This posts you one such mistake and how to fix it.
3. Email Personalization Not Working? Read This
   This posts explains why the email personalization might not work. The bottom line is that you have update your personalization criteria over time and test it.
4. 3 Techniques for Expanding your Email Reach
   Email marketers are facing a tough time with growing emails remaining unopened and unsubscribes. Acquiring new subscribers using old techniques is expensive. In this post I have listed 3 techniques that you can use to spread the word of your emails/newsletters beyond the email list that you are sending the emails to.
5. Are You Depleting Your Email List?
   Email marketers, in order to maximize short term conversions, often bombard irrelevant emails in subscribers inbox However this short term mentality results in erosion of long term viability of their email marketing, due to increase in unsubscribes causing depletion of email lists.
6. 15 Things to Test in your Email Campaign
   This post talks about 15 things you can test today.
7. Targeting Cart Abandonment by Email
   Targeting Cart Abandonment is a great way to drive conversions however, use incentives/offers cautiously.
8. Conversion Tip: Making the Most of the Email Confirmation Thank you Page
   Use your Confirmation page effectively, this posts shows an example of a good page and a not so good page.
9. Number One Email Marketing Mistake
   Number one mistake marketers make with email marketing is to send “Irrelevant” messages to their customers. Find out why this strategy has a far-reaching impact on your email marketing program.
10. 7 Ways to Create Relevancy in Emails
    7 tried and tested ways of creating relevancy in emails are described in this post.
11. Relevancy Matters in Email Marketing
    This post shows an example of an email that missed the opportunity to convert.

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9 Facebook Post Engagement Killers

Have you wondered why you are getting a very low engagement on your Facebook posts?  Here are nine common reasons that result in low Facebook post engagement and tips on how to fix them.

1. You are posting on wrong day and time – You should time your posts according to your audience’s (fans/targets) most active time on social media. If you are posting your messages when majority of your audience is not active then you are not achieving the maximum benefit from your posts. Below is an infograph that is based on analysis conducted by Bridge.com,  which provides general information about the best time for Facebook posts.
   However, rather than blindly accepting these suggestions, you should use your own data to figure out the best day and time to posts. There are several tools that will allow you to see when your audience is most active. For example, simply Measured provides you stats such as “Top Day For Comments” and “Top Time For Comments”.
   
2. You are posting too many or too few posts – As shown by the Track Social (image below), the more you post in a day the lower is the engagement. According to SocialBakers.com, if you post fewer then 2 posts a week, you will not engage your audience enough and you will lose engagement. If you post more then 2 per day (as a brand) you also will typically lose engagement. That means the ideal number is between 5 – 10 posts per week as a brand, and as a media company, this is typically 4 – 10× higher, as news are information people engage with all day long. However, you should not just rely on industry data, instead try to look at your own data to figure out the best frequency for your posts.
   
3. You are not posting engaging messages – Before preparing your post, think about who are you trying to reach and why will they care about what you are posting. Give them a reason to engage with your posts. If you a grocery store and promote a can of beans at regular price, then do you think you will get any engagement? Give them something to engage about. Give them more than just an image of the product. May be show some urgency on why they should click on the image, watch the video, click on the link, share or comment. Think about other ways to prompt then to take actions – Is there a limited time offer? Is this a limited edition product? Is this fresh crop? Here is an example of two post by PCC Market in Redmond:
   

This post had just 22 likes even tough the page has 45,800 fans. Why is that? Likely because there is nothing for fans to get engaged with?




This post on the other hand a lot higher engagement (though it can still be improved). There is a sense of urgency here “Seasons First Catch of fresh halibut” and there is link to halibut recipes (a call to action, see below).  Also, it is possible that PCC has more halibut lovers than mushroom lovers. The key is to understand your audience and give them something relevant and engaging.

4. There is no call to action or links – Call to actions prompts audience to engage. Ask and you shall receive. Ask them to click on a link, like a photo, participate in the giveaway are some of the examples to get you fans/followers to take action. The post of mushrooms above has no call to action. What is PCC expecting from the fans? Just posting a picture is not going to work, provide a call to action.
5. You don’t have the right fans/followers – This generally happens when you pay to acquire fans. People who do not like your page organically are less like to be engaged with your posts. Also, paid Fans not always genuine, according to Huffington Post, you might be getting fake users to like your pages.
6. You are relying on organic reach – Organic reach has been declining in Facebook. According to Oglvy report, the organic reach was about 6% for pages less than 500K fans and 2% for pages with over 500K fans. This reach is a lot lower today. Lower reach results in lower engagement. This means that if you want your fans to see your post then you will have to pay Facebook to put your post in front of them.
7. You are targeting the wrong people – As you decide to promote your post by using paid ads on Facebook, you might be trying to maximize reach (within you budget) and in doing so might be reaching people who are not likely interested in your brand/product/post. In this case the impressions of your paid post are increasing but you are not getting any clicks/like/comments/share.
8. Your content looks too much like an “Ad” – You are pushing ads for your brand and products and your posts look too much like advertisements. People are ad blind, according to Techcrunch article,  6 in 10 people totally ignore the ads. Do not just push ads, follow tip on this page and make people engage with your post.
9. You are not using video – Photos used to be the king of engagement on Facebook, now pretty much everybody is using them. According to analysis done by Quintly, videos generate more engagement followed by photos.
   

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Other Social Media posts that you might have missed:

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• Sentiment Indicator: Social Media KPI
• Social Media Sentiment: Don’t Get Caught Up In Raw Counts
• Value of Social Shares
• 3 Tools for Measuring the Virality of Your Content
• Free Social Media Monitoring Tools for Small Businesses
• Social Media Analytics Part I
• Do Number of Likes and Followers Matter?

Three Tips for Choosing the Colors for Data Visualization

Colors can add to your data visualization and make the story stand out or they can distract the audience from the main message. It all depends on what colors you chose and how you use them. In this post, I am listing three things to keep in mind when creating your next data visualization. I am not guiding you specifically on what colors (hue, value and chroma) to use but three things to keep in mind when selecting the colors:

1. Use conventional colors:  Generally red color means negative or a bad value and green means positive or a good value.  Choosing the default colors as presented by your visualization tool might not convey this meaning in all the cases.  Say, for example in Tableau, when you choose the default “Red-Green Diverging” color from the pallet, the red represents the smallest number while green represents the largest number, and it changes from red to green for the values in between. This generally works fine.  Where this becomes an issue is when smaller numbers are actually better than the larger numbers. For example, when you are showing Cost Per Click, lower is better so it should be Green while higher numbers are bad, hence they should be Red. Leaving the default will show low CPC as red, while higher CPC will be green, this will convey the wrong message to someone who is just glancing at the visual. To fix this issue in this case, all you have to do is just check the box, titled “Reversed” to reverse the colors, now Red will be used for higher value.
2. Don’t use too many colors: Using too many colors can distract the consumer of the visualization from the main message. Minimize the number of colors you use in your visualization. (See guidelines for selecting colors section in “Expert Color Choices for Presenting Data” paper by Maureen Stone)
3. Make main message/data to stand out:  Make sure the color combinations you chose enables you to make the main message to stand out. For example, white on black will stand out while grey on black might be lost.

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5 Data Quality Issues To Watch Out For

We all know that wrong data leads to wrong analysis and hence can cost a lot of money.   In this post I am highlighting 5 issues that lead to wrong data and hence wrong analysis.  Make sure you take care of these issues before spending any time on analyzing and putting your presentation together.

1. Manual entry by end users – When you rely on the end users/customer to enter the data in the free form you will get lot of variations of the data. For example, when you ask them to enter the city, you can get variations such as Redmond, Redmond WA.  Redmond (Seattle), Remond etc.  Doing any analysis on the city level will pose an issues since you have several variation of the same city. Unless you have thoroughly cleaned and accounted for every possible variation you will not have the right analysis. In order to avoid such issues, wherever possible provide the choices via drop down or auto-fill rather than letting users type in the answers.
2. Manual entry by someone in the organization – Though this is more controlled than letting end users enter the data, you still have issues similar to number 1 above.
3. Excel sheets (calculations) – This becomes an issue when you have lot of calculated columns and some of them are dependent on the other calculated columns and sheets.  One simple mistake can cascade to multiple columns and can mess up all your analysis.  Whenever possible, do not rely on calculated columns (prepared by someone else) in excel sheet, just use the raw data and do your own calculations so that you can stand behind them.
4. Data Imports, connections and processing – In most companies the data resides in various places – databases, excel sheets, flat files Hadoop, 3rd parties etc. For you to get a 360 views you will need to collect and combine the data for all the sources. The data corruption can occur at several places including but not limited to mapping wrong keys, missing some key data, writing wrong queries, importing partial data etc.  You should always verify the data that you are getting and make sure that it is clean and complete. Since there are several owners of the data this is not always an easy task, particularly in the large organizations.  There is not much that you can do on daily basis to verify the quality of the data, but make sure you understand the underlying data sources and have good understanding of the process that is used to combine the data.  Make sure that you in loop on any changes that are being made to the data sources and the process. You can not afford for your raw material (data) to be of a low quality.
5. Visualization tools – You expect these tools to work, don’t you? However be careful and double check your calculations before you present your data.  I recently had two issues that made me believe that there are many of you who will run into these issues and might present the wrong analysis.
   • When you use averages makes sure that you are using the right columns.  Average of an average is not the same as average by summing the values in individual rows.  Recently I ran into a situation where CPM (Cost Per Thousand Impressions) was already calculated in the excel sheet (see Issue no. 3 above).  When that data was brought over in Tableau, the analyst, in an effort to find average CPM, used the calculated column to compute average CPM.  Everything looked good on the surface but it was wrong since it calculated average of an average.
   • When using a map make sure you use the correct values of Longitude and Latitude. I saw an example where the map showed up perfectly, however a quick quality check showed that the average value for a state was more than the individual values of all cities in that state, which is not possible.  On further investigation we found that the issue was with the way Longitude and Latitude were used to render that map. Once the issue was fixed, everything worked fine.

I would love to hear from you if you have encountered these or any other sources of data quality issues.

A Simple Fix To Grow Your Email List

Are you loosing your email subscribers right after they are signing up? If yes then you might be making a similar mistake that I encountered recently. Here is what happened to me:
I submitted my info on coolinfographics.com to download a free chapter of the book. After I filled the form, I got a message that I will get an email with a link to the download.  I eagerly waited for the email to arrive. As soon as I got the email, I opened it and quickly clicked on a very prominent and long link. I was expecting to see a page where I will either be able to download the chapter or my download will automatically start. Instead I got the following message:

What???? What just happened?
Turns out that the long prominent link in this email was not the link to download the sample chapter, instead it was an Unsubscribe link.  So I accidentally unsubscribed from the mailing list I subscribed only few minutes ago.  I am sure, I am not the only one who has done that. I wonder how many subscribers is this site is losing due the design of this email?

Here are two mistakes in this email

1. The unsubscribe link is bigger and more prominent than the actual download link (main Call to Action).  My eyes directly went to the long link and without even thinking twice, I clicked on it.
2. Transactional Emails do not require you to have an unsubscribe link (See http://www.spamresource.com/2009/12/is-unsubscribe-link-required.html). Since this is a transactional email so you don’t need give an option to unsubscribe.  You can argue that it is a best practice to provide an Unsubscribe link. Sure if you want to provide an option then make it a small in font and length.

Fixing the problem:

Simple solution is to remove the attention from Unsubscribe link and make the main Call to Action (Link to Download) stand out, see below for a revised version:

  

What do you think? Questions? Comments?

BTW: If you are interested in data visualization then go ahead and check the sample chapter or buy the Cool Infographics: Effective Communication with Data Visualization and Design at Amazon.