In this digital world, marketing is a profound way to increase sales and … and wants of customers in real-time is a basic online marketing technique.
How to Utilize Real-Time Data in Your Marketing Efforts
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How to Utilize Real-Time Data in Your Marketing Efforts
How to Utilize Real-Time Data in Your Marketing Efforts
How Marketing Can Be Better Automated With Big Data
Marketing automation is the next big thing. In mid-2013, Salesforce announced the acquisition of ExactTarget which owns Pardot, the marketing automation company whose software-as-a-service application has enabled thousands of companies to automate and manage their online marketing campaigns and boost efficiency. Before this, Adobe had acquired Neolane, another cross-channel campaign management and marketing automation provider while Oracle had acquired Eloqua and Responsys who are leaders in the cloud-based marketing automation space.
It is not hard to understand the mad rush in owning applications and services that help customers automate their marketing campaigns. Not too long ago, online marketing formed a small subset of a business’ larger marketing strategy. Today, not only is online marketing a category onto itself, it is also getting increasingly diversified through channels like PPC, social media, SEO, content marketing to name a broad few. This space is getting increasingly cluttered and without proper automation tools, it can get extremely difficult for businesses to manage and ensure consistency in the various inbound and outbound marketing messages.
Besides this, there are several other benefits to marketing automation: it can drastically improve the efficiency of the sales team and their sales cycle, it saves time and money in mundane marketing administrative tasks including generating reports and sending bulk email communications, improves the targeting and messaging without the need for additional resources and accelerates close rates through persistent follow-ups. While a lot of SaaS-based marketing automation tools have enabled such efficiency improvements in the past, the next step in this industry is to use big data and cloud computing to create a vastly improved marketing automation solution. Here are some areas that marketing automation businesses are working on.
Data Driven Messaging: Marketing automation today largely relies on the marketer setting filters to target prospects and customers through parameters like their location, time zone, purchasing frequency, etc. But marketing communication could become more timely and efficient if it was based on analyzing their buying behavior not just on the marketer’s own website, but also over other complementary channels. This does not necessarily have to be a privacy nightmare for the customer. Tools like BuiltWith already host tons of valuable information regarding the back-end technology infrastructure and business tools used by various businesses. This information from thousands of businesses may be mined using big data to derive crucial insights into potential buying patterns of your existing or prospective customers and marketing strategies may be automated around this.
Predictive Analytics: Marketing strategy today is based off data provided by goals and funnels. While they provide a reactive way to analyze the success of marketing campaigns, big data can help with building proactive marketing automation systems that can yield higher returns on your investments. For instance, big data analytics can tell you whether the navigational path taken by a prospective customer would lead to them signing up or not. Based on this, you can devise an email marketing campaign that could route your prospects through a navigational path that is better suited to bringing them ‘back on track’.
This is an exciting time to get started with marketing automation and with new big data driven strategies, marketing would not only get more efficient, but also smarter.
How Marketing Can Be Better Automated With Big Data
New Data Proves Facebook Ads Lift Search ROI
Facebook has just released some new research that shows us just how well Facebook ads play with others, like paid and organic search channels, to lift traffic and conversions. As a long time search geek who has just recently gotten really into Facebook ads, this data makes me really happy.
So sit back, relax, and let me take you on a magical ride through Facebook’s awesome new data.
Holy Mobile, Batman! Mobile Facebook Ads Lift Search Referral Volume
There’s no “Batmobile” without “mobile” – and mobile is a big part of the equation here, too.
In the first segment of its newly published research, here’s what Facebook discovered that “mobile-heavy Facebook paid media exposure caused a statistically significant lift in search referral traffic volume to advertiser websites, predominantly on mobile.”
6 Fast Facts
1. Consumers who were exposed to Facebook ads were more likely to conduct a new search on mobile.
2. Referral search traffic climbed to 12.8 percent in some cases.
3. The average lift for mobile search referral traffic was 6 percent.
4. The average lift for desktop search referral traffic was less than 1 percent (but the study points out that since 70 percent of Facebook ads were in a mobile format, this data is consistent with the “same-device stickiness” in the consumer journey that is typical for e-commerce).
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5. Small businesses saw the largest variance in lift.
6. Facebook says there’s more research to be done: “We hypothesize that lift in search traffic due to Facebook paid media exposure may correlate with a combination of other factors, such as organic content, the reach and frequency of the Facebook campaign, the amount of paid search media weight and other digital or media weight during the campaign period.”
Cars, Money, Shopping
No, that’s not just a typical day in the life of a Kardashian – it’s the sectors that Facebook looked at in the next segment of its research: “For brands in automotive, financial services and retail, we found that Facebook paid media caused statistically significant lift in lower-funnel KPIs these advertisers care about, including online and offline sales.”
5 Fast Facts
1. Auto sector: When consumers were exposed to Facebook ads, they were more likely to search for branded keywords versus non-branded keywords. Facebook says the result of this search behavior made search ads almost 2 percent more effective for those studied (because branded keywords cost less than other keywords).
2. Financial services: Research found a 19 percent lift in paid search conversion volume and a 10 percent improvement in CPA with exposure to Facebook ads!
3. Retail space: Findings show significant boost in search return on ad spend (ROAS) in markets that included Facebook ads exposure.
4. Average order value grew from search conversions when paired with Facebook ads. Facebook says, “We can hypothesize that people seemed more comfortable spending more after first being exposed to Facebook paid media.”
5. Searches for physical store locations grew after exposure to Facebook ads. “We found that when people saw Facebook ads in addition to paid-search results, they were not only 13 percent more likely to buy online, they were also 79 percent more likely to seek out the brand’s physical store.”
TL;DR and Recommendations
Like we’ve known for years, multiple channels work together in your customer’s journey and Facebook ads are no exception.
Of note is the impact of the mobile device in all of this, which, as the research points out, is no surprise as people go on to search from their mobile device when they’ve been served Facebook ads on mobile.
I’ll leave you with a few recommendations based on the data, and you can download the full research here.
- Create a story. Research suggest that “coordinating the timing, copy and messaging across both digital marketing channels, Facebook and search,” can help in driving traffic and conversions.
- Measure all the things! Track the cross-channel effects of Facebook ads and search, especially watching mobile because “the resulting lift in search behavior from Facebook paid media exposure is disproportionately higher in mobile on average.”
- Test and allocate budget. Facebook writes that “by applying a sufficient budget on these digital channels, a marketer could use Facebook to help drive discovery on Facebook and ultimately improve search objectives.”
So get out there and start testing ads on Facebook!
New Data Proves Facebook Ads Lift Search ROI
How to Boost Email Marketing ROI? Put Your Customer Data to Work
Only 20 percent of marketers use behavioral triggers to accompany their email marketing strategies, according to Econsultancy. Past issues with implementation and the lack of comprehension of the outcomes email triggers can drive on behalf of the e-commerce company have led many email marketers to believe the many misconceptions about trigger emails.
With data come opportunities
The expectation of today’s marketers is to monitor the analytics of their campaigns to ensure they are providing a positive ROI as compared to their investment in a specific channel. The industry has reached an inflection point where marketers need to know how to take action on their data and understand the technologies available to help them better facilitate driving results from company data.
Referring to analytics is often the starting step to discovering value in your customer data for many marketers, whether it is through Google Analytics, Omniture, or an alternative tracking platform, and to begin getting into the performance of your various conversion funnels. Larger organizations may have business teams devoted to analyzing and segmenting this data.
A frequently overlooked source of vital data can be taken directly from your product catalogs. Both customer behaviors and changes to the product catalog will show trends around failed conversions, customer drop-off points or out-of-stock products. These are potential opportunities to reengage with your shoppers and help influence them to convert with automated emails.
For example, many e-commerce companies find data that suggests their shoppers start an order but do not complete their purchase. This shopping cart abandonment data can demonstrate a great amount of lost opportunity revenue. With some companies reporting that up to 74 percent of shopping carts are left abandoned, it is not an uncommon problem.
Through analyzing your conversion funnels and customer data, you can better distinguish where behavioral triggers can help to drive ROI. For example, Serena & Lily aimed to tackle lost opportunities that they found in their data by triggering the following email when a shopper abandons her order.
Serena & Lily attempts to increase revenue through targeting shoppers who failed to complete their transaction.
In addition to a reminder, Serena & Lily also offers free shipping to better incentivize their shoppers to return and make a specific purchase. While offering incentives can improve the effectiveness of a specific triggered email, it is recommended you test a variety of these tactics to determine which fit best with your marketing and revenue goals.
Triggered email implementation = increased ROI
While improving metrics for open, click through, and conversion rates for automated emails is important, perhaps what is most notable is that automated emails generated nearly three times more revenue than their manually delivered counterparts.
Automated emails are often more effective because your brand can target your audience based on their behavioral data, meaning that you can send more relevant and personalized content to your shoppers while your company is already top of mind.
For example, let’s say a shopper recently purchased a pair of Herringbone suit pants from Perry Ellis. By sending an automated follow-up email, Perry Ellis now possesses the opportunity to upsell and create more revenue by catering this email content to the details that the shopper provided at checkout.
Perry Ellis appeals to its shoppers’ interests by promoting related products with partial discounts.
The retailer also takes advantage of customer data to better comprehend what products are related or frequently purchased together and can use this to provide more interesting content to its shoppers. The more personalized the email, the more likely it will resonate with the shopper and create positive actions.
It’s also vital to understand the difference between trigger emails that drive engagement and immediate revenue for your business. For example, many post purchase emails are typically more focused on engagement, satisfaction and driving revenue in the long-term like a survey or content centered around better using a product recently purchased, than they are on generating immediate revenue from an existing customer like a related products trigger.
The difference in whether a trigger drives action or revenue is completely dependent on the company, the typical product order value, and the objective they are trying to achieve. Triggers are flexible when you have a system that allows you to rapidly adjust dependent on the feedback you’re receiving from your customer and product catalog data.
To best drive revenue for you company, prioritize the customer behaviors that are stopping conversions and develop personalized triggered emails that help escort your shoppers through your sales funnels. Evaluate the interests and needs of your shoppers when designing these emails to better increase opens, click through rates and the ROI of your email marketing campaigns.
Ryan Luckin is head of marketing and communications for Bluecore, a marketing automation solutions provider.
How to Boost Email Marketing ROI? Put Your Customer Data to Work
Factual Announces Deals With Apple And Facebook For Improved Location Data
Marketers and publishers are just starting to understand that as the cookie was to desktop advertising, location data is to mobile. Location history is evolving into a kind of cookie substitute for mobile advertising, but one that is more accurate and powerful than cookies.
This goes way beyond the archetypal mobile-location use case (“you’re walking by a Starbucks…”). However most brands and marketers still think more conventionally about location in terms of real-time geofencing or proximity targeting.
“When it comes to mobile, location is the critical piece of data that’s underutilized,” explains Factual CEO Gil Elbaz. Factual, which now refers to itself as a “location platform,” just announced expanded location-data deals with Facebook and Apple:
Our data stack is designed to distill down billions of pieces of information from millions of different sources into a clean, comprehensive, up to date database of places in 50 countries. It incorporates new inputs in real-time and can quickly rebuild the entire data set as we improve the data stack itself, giving us an incredible amount of flexibility and agility in building data. The sophistication of our data stack and resulting flexibility and agility improves our ability to provide better and more timely data to Apple Maps.
Better places data is a small though critical part of the story. More interesting is how location can unlock specific audiences, even hyper-targeted audiences. Factual has built a large number of “off the shelf” audience segments that it makes available to partners, such as in-market auto buyers, heavy QSR patrons and business travelers among many others.
Factual can also create custom segments, which illustrate the potential of location intelligence. For example, the company recently helped a major US theme park identify the top 10 countries where its visitors came from. These insights then allowed the theme park to target leisure travelers in their home countries and find lookalike audiences of potential visitors.
Other examples of targeting very specific audiences include people who’ve visited a dentist in the past month or female yoga enthusiasts. Such specialized audience categories would be difficult if not impossible to reliably target on the desktop.
There are a number of platforms and providers that share this vision of location as a doorway into audience segmentation and targeting (among other use cases). Beyond Factual, a non-exhaustive list includes Moasis, NinthDecimal, Placed, PlaceIQ, Skyhook, ThinkNear, Verve, xAd and YP.
Buyers and agencies are gradually becoming more educated about the possibilities. They’re starting to use location as a way to gain insights about customer behavior, as an analytics tool to determine the effectiveness of other media channels (e.g., TV and outdoor), as well as a way to reach prospects any time and place — not just when they’re within a mile of a Best Buy or a Starbucks.
(Some images used under license from Shutterstock.com.)
Factual Announces Deals With Apple And Facebook For Improved Location Data
Social Media Communication: Concepts, Practices, Data, Law and Ethics
In Social Media Communication: Concepts, Practices, Data, Law and Ethics, Jeremy Harris Lipschultz presents a wide-scale, interdisciplinary analysis and guide to social media. Examining platforms such as Twitter, Facebook, LinkedIn, Pinterest, Youtube and Vine, the book explores and analyzes journalism, broadcasting, public relations, advertising and marketing. Lipschultz focuses on key concepts, best practices, data analyses, law and ethics—all promoting the critical thinking professionals and students need to use new networking tools effectively and to navigate social and mobile media spaces. Featuring contemporary case studies, essays from some of the industry’s leading social media innovators, and a comprehensive glossary, this practical, multipurpose textbook gives readers the resources they’ll need to both evaluate and utilize current and future forms of social media.
For more information about the book, supplementary updates and teaching materials, follow Social Media Communication online at:
Facebook:
https://www.facebook.com/SocialMediaCommunication
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@JeremyHL #smc2015
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http://www.slideshare.net/jeremylipschultz
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Social Media Communication: Concepts, Practices, Data, Law and Ethics
Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More
How can you tap into the wealth of social web data to discover who’s making connections with whom, what they’re talking about, and where they’re located? With this expanded and thoroughly revised edition, you’ll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs.
- Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites
- Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data
- Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects
- Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit
- Take advantage of more than two-dozen Twitter recipes, presented in O’Reilly’s popular “problem/solution/discussion” cookbook format
The example code for this unique data science book is maintained in a public GitHub repository. It’s designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.
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Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More
3 Smart Ways to Maximize Marketing with Social Data
Social media provides marketers with more data than ever before, and it’s all delivered in real time. I recently teamed up with B2B marketing speaker and author, Paul Dunay, on a RingLead webinar to discuss the topic of using social data as a B2B marketer, as well as how to avoid certain pitfalls.
1. Ensure quality data before measuring
Speaking of pitfalls, we’ve all run into the typical bad data story where you send an email and it reaches the wrong person, or the right person with the wrong name. Bad data ultimately impacts your marketing credibility, and in today’s B2B SaaS market, it’s all about relationships and credibility.
Whether it’s poor targeting, poor segmenting, or poor use of data, bad data will always impact your marketing efforts. While it’s tough to be 100% rid of bad data, you must start somewhere. Sit down as an organization and understand that cleaning your data is not something you do once a year; it’s a constant process. Consider all of your different data points and how they’re connected. Automate your data quality processes with technology. This will ensure data integrity, which is at the core of your marketing.
Set a budget for data quality now, and make it an ongoing program. Don’t wait until you make a fatal marketing mistake that ruins the credibility you worked so hard to establish. Paul Dunay’s tip is to remember that the belly of marketing is typically in the summer months, so use that time to start cleaning your data.
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“The growth of data within companies is around 40% a year, and the cost of bad data is in the trillions of dollars. That is twice the amount of the federal deficit. Try to stay ahead of it.” — Paul Dunay
Bad data exists in your database now, so you need to do some course correction.
2. Set your metrics, goals and expectations upfront
When you’re looking at social media, there’s a big difference between data and insights. While social insights are in the eye of the beholder, you can set goals upfront, and work to meet those expectations. This approach will give you real insights.
Paul Dunay recommends that getting started with social insights requires knowing your sources. For instance, are you getting the full Twitter fire hose or are you getting 10% of it? Although that may seem like a small data point, these details can have a major impact on the data. In the example of the Twitter fire hose, there’s a big difference between real time data and data delayed by a few minutes or more.
Go beyond the basics
Choosing your social metrics requires going beyond likes and clicks. Social engagement is one part of the story, and the other part is about the people. When analyzing campaigns, don’t just look at engagement metrics such as likes and clicks, but look at who is engaging. A ton of clicks or likes could be a false positive if you’re not reaching the right audience.
Try to formulate a hypothesis on what is, or what could be on social media, and then see if the results match up. This helps you set expectations, because although you want your content to kill it, you need an actual and realistic starting point.
3. Merge social data with other marketing data
As Paul shares, “The devil is in the details, and the combination of social data and customer data can be very powerful.” Your marketing automation system can pull your website and email data, so now it’s about combining social profiles in the process. Start doing this with progressive profiling and asking for more information, such as Twitter handles or LinkedIn profiles in your web form fields.
Request the social data that makes the most sense to your brand. Test the process of authenticating web forms with social profiles. Get your operational ducks in a row in order to leverage the necessary data, such as UTM tags, referral source, lead source, etc. Get the data you need to connect those dots because ultimately, you want to authenticate the lead to ensure it’s the right lead. These insights help you confirm that you reached this person through social, and through a specific campaign. Then, you can further dissect the social channels to obtain more data about your prospects and customers. All of this will ultimately allow you to better target, nurture, and find more of the right contacts.
Accurately set up your social efforts, data and tracking from the start to make sure that you’re able to get that data to tell the accurate story. Without all of the pieces, you might be telling the wrong story.
Utilize personal emails
As a B2B marketer, you work hard to promote lead generation through social media, only to get frustrated by form completes using personal addresses like Gmail. However, I encourage you to look at those email addresses in a new way. Personal email addresses are associated with your prospects’ social profiles, so they are actually great tools for targeting on social networks. Those addresses give you a key piece of information about how to reach them directly on Facebook or Twitter. In a recent campaign, I realized that 65% of the email addresses were Gmail. Instead of discarding them, I checked to see how many of those Gmail addresses synced up to my prospects’ social profiles, and amazingly enough, about 80% synced up. I suddenly hit a gold mine and found a better way to target those prospects.
No matter how you you think about combining social media with data, always consider how you can use that data to get smart about how you target.
Get more marketing lessons for lead generation in the free ebook below.
3 Smart Ways to Maximize Marketing with Social Data
Facebook Inc Says Rainbow Filter Was Not A Marketing Or Data Gathering Stunt
Facebook Inc.’s (NASDAQ:FB) recent move, to allow users to apply a rainbow filter on their profile pictures, has garnered sharp criticism. The new option followed the nationwide legalization of same-sex marriages in the US, and was aimed to show solidarity with the movement.
The social media giant clarified that the new filter has been adopted to show support for the Supreme Court’s decision, and is not an advertising stunt, or a way to gather key information about its users.
In an official media statement, a Facebook spokesperson claimed that the tool was “something that enables people to show their support of the LGBTQ community on Facebook.”
The “celebrate pride” tool was launched by two company interns before the New York pride parade. It caught on like wild fire once the new profile picture color scheme was adopted by the White House. The White House changed its Facebook page’s profile picture to depict President Obama’s support for the latest constitutional law.
In a Facebook post, President Obama claimed: “Today is a big step in our march toward equality. Gay and lesbian couples now have the right to marry, just like anyone else.”
The rainbow filter gained immense popularity on the social networking site, and was immediately adopted by numerous Facebook users and popular celebrities, including Leonardo DiCaprio and Anne Hathaway.
Facebook also received criticism for using the new profile picture filter trend as a tool to gather information, and user details, to boost advertising on the platform.
According to Mashable’s reports, Facebook claimed: “We aren’t going to use this as a way to target ads and the point of this tool is not to get information about people.”
The company clarified that contradictory to accusations made by MIT scientist Cesar Hidalgo, who claimed that the filter’s introduction had been more of an “experiment,” compared to just a social cause, its motives had nothing to do with advertising.
CEO Mark Zuckerberg wrote: “I’m so happy for all of my friends and everyone in our community who can finally celebrate their love and be recognized as equal couples under the law.”
Almost 26 million Facebook users changed their profile picture to celebrate the same-sex marriage ruling.
Facebook Inc Says Rainbow Filter Was Not A Marketing Or Data Gathering Stunt
Implementing JSON-LD Structured Data in your E-Mail Marketing Campaigns
E-mail, JSON-LD, and Structured Data
Implementing schemas on websites are a great way of enriching structured data, and has been for the past few years. Schema by no means is an easy task to implement especially if you have no web development background. Recently Google has announced another format of implementing schema utilizing the javascript format “JSON-LD” to make implementing a bit easier. Many web marketers have had success implementing JSON-LD within websites. What is even more impressive are marketers are pushing the envelope, utilizing the new schema format in advanced ways to provide rich insights. We have seen semantic data that can be dynamically pushed from Google Tag Manager to a website, thus sending the data to Google Analytics for measurement. However what is not as well know is implementing JSON-LD within your e-mail marketing campaigns to provide a better user experience and rich data.
Unlocking the Full Potential of E-mails
There is a new generation of digital marketers that feel e-mail marketing is old school. However, e-mail marketing is still one of the preferred digital marketing techniques used to date. Email is an important part of how we get things done.
We check our e-mails hundreds of times a week. We plan trips, organize events, check-in with flights and much more. For a while Google has made it apparent that they are moving towards enriching all data as much as possible. Why not emails right? Adding schema.org markup to your e-mails will create a better user experience by adding quick actions, check-in times, reservation actions and more. Google’s Inbox, Search, Calendar, and Google Now all use structured data. You can now start enriching your data as well!
Apps Script
To start it is best to test your schema e-mail markup by sending an e-mail to yourself. First visit scripts.google.com. You will be redirected to the information page if it is your first time. Begin by clicking on Start Scripting which will bring you to the script editor. From there create a script for Blank Project.
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Next you will want to replace the code that is in “Code.gs” with the following:
Next you will want to select File > New > Html file. The important part here is to name the file “mail_template” which matches the parameter in the javascript shown in the picture above. Replace the content of the HTML file with the following, however just remember to change your own “URL” and “target” to whatever you would like for test purposes.
Testing the Structured Data
Remember in math class, when the professor always talked about “checking your work”? Well that is a rule I still commit to, day in and day out when it comes to script. JSON-LD, scripts, and coding can work well when it wants to. However all it takes is for one misplaced comma and the script will not fire correctly. Therefore we need to check our work. To test we need to save the project. Next select the tab “Code.gs” which is on the left side of the script page. Here you want to make sure the function “testSchemas” is selected in the “Select Function” dropdown menu.
After you run the script you’ll be asked to grant authorization. After that you will need to re-run the script. At this point you should check your inbox. You should see an e-mail from yourself with a “Go-to Action” button like I have shown below!
Registering with all mighty Google
So now that you have that down, its time to register with Google which is a pretty simple process. Currently Google lets you send e-mails with scripts embed to yourself strictly for testing purposes. However, if you would like to start using this for your users in your e-mail marketing campaigns you will need to register with Google and follow their steps. Its pretty easy. Head on over to developers.google.com to set up the registration process!
Whether you are email marketing for a large business that needs to send out reservation e-mail markup to your next event; or an individual on a job search that would like to increase his/her CTR to their resume in emails. Everyone can benefit from JSON-LD structured e-mail markup.
Implementing JSON-LD Structured Data in your E-Mail Marketing Campaigns
Content Marketing by Connecting the Data Dots
One of the biggest challenges of marketing anything online is integrating data (i.e., managing, interpreting, connecting and efficiently acting on all data) you have access to in the quickest way possible to make the most of each of your investments. The challenge in managing online marketing lies in being able to connect one insight from one source to another insight from a different source to devise the best strategy possible.
Disjointed Data Creates a Jumbled Picture
Imagine you have high engagement for a twitter campaign in which you invested X dollars. You’ve acquired new followers on your Twitter account, so that’s one KPI, but what about clicks to your campaign’s landing page?
You can also see that Y number of people landed on the website by way of that Twitter campaign, so you’ve also increased traffic—another KPI.
But who are those people that visited? Have they visited before? What’s more, how do you retarget them? Via an email campaign? A message on LinkedIn or Twitter? Finally, how do you filter through the noise so that you do not waste resources on dead ends? And how do you do that without spending hours figuring it out?
There are a lot of tools out there that claim to do everything, and many of them have very complete systems—particularly when it comes to managing marketing automation. In many cases, however, such software carries pricey licenses, making it unfeasible for both small and large companies.
Moreover, most tools focus heavily on one particular strength—whether it’s listening, content curation, amplification, social media management, tracking users’ activity, identifying users or facilitating and automating email marketing.
So, as a marketer trying to build an efficient system whereby you’ll get the most out of your communication and marketing investments, how do you address these issues? Whether your company has a large budget to invest in a completely integrated system or you have to make due with previously purchased tools and build a system piece by piece on your own, the questions are the same:
- Where are you hemorrhaging data?
- Are you under-utilizing available resources?
- How easy is it to connect data from one tool to the next?
1. Make the Most of the Data You Have
No matter what type of campaign you’re executing, you need to track all the data associated with each element of communication for every channel you utilize.
Can you answer the following questions for each new content piece you create and distribute?
What kind of content works?
What are the tone, topic and format of your best content pieces? The answers give you an indication of which subjects are the most interesting for your audiences so that you can produce more in the same vein.
Where did you receive the most conversions?
Was it a social media campaign, AdWords or a display campaign? Paired with sentiment analysis above, you can discern two things: X content is really effective on Y channel. Next time, you will know what kind of content to promote and the best way/platform to share it.
Who did you attract?
This is the most challenging part, so you’ll need to rely on tools that combine tracking and databases to give you the best idea about who is coming to your site. The real challenge is figuring out which one best suits your business needs.
At the most basic level, you should track IP addresses to identify the companies visiting your site. If you have an internal database, you should also track at an individual level to further understand who they are (e.g. the CMO at Company X) and how best to reach them (e.g. email, social media or phone).
What was the reaction to your communication?
Listening tools are a powerful way to learn what’s trending and determine which topics to touch on in your content strategy. It’s also a nice way to gauge whether you are making an impression (positive or negative) within your target communities.
2. Encourage Employee Advocacy
Employee advocacy boosts your content marketing strategy by:
- serving as a test pool for your contents’ appeal
- increasing the organic reach of your content without spending more on paid media
- increasing the trust associated with your content (because it is a form of word of mouth marketing)
Whether you are already engaged in employee advocacy or just getting started, the following steps are crucial to get the most out of your efforts: track, track and track. Make sure your employee advocacy tool can do the following:
- Track the kinds of content being shared among employees, as well as end user audiences. This allows you to compare listening tool data with sharing data. It can also help refine the topics in your content calendar.
- Track the reach and engagement generated by your employees.Celebrate the work of employees who continually write engaging posts that gain a lot of traction on social media. This not only rewards those who are succeeding, but also helps educate employees on the best tactics and practices.
- Target your content to the right employees. Employees are more likely to share content that is relevant to them. Each business unit that is engaged in your employee advocacy initiative should be creating and sharing marketing content that makes sense to them and their respective job functions.
3. Connect the Data Dots
Before you take the time and effort to build a workflow around tools and the data they help manage, it’s essential that you understand how (if at all) they integrate with one with another.
Total integration isn’t always possible, but if you can at least connect a group of tools (e.g. social media campaigns that feed into lead tracking tools and CRM systems or listening tools and content marketing databases that connect with employee advocacy and amplification platforms) then you are almost there.
The idea is to track content from its point of origin to the point of engagement, which then triggers an outbound marketing treatment or kicks off a lead nurturing cycle. It’s better to determine that integration isn’t possible early on and avoid the tool altogether than to be knee-deep in a campaign with mountains of data that you can’t take action on.
Focus on the Big Picture
The most important point to draw from all of this is to make sure you build a system that makes sense for your workflow and your company’s current capacity—whether it’s in terms of human resources, budget or scope of marketing activity.
Don’t over-invest in tools you do not need, but rather look at what you are doing now and find out where you need to plug the data leaks. Power your current marketing activities by making sure you are making the most of every single click and potential lead by finding a way to collect, connect and evaluate your data. That’s the aim of the game.
Content Marketing by Connecting the Data Dots
How Can CMOs Make Sense of Big Data?
As with so many other areas of the modern economy, marketing has been revolutionized in the past few years by the growth of data analytics. Marketing teams and chief marketing officers (CMOs) are using big data for search engine optimization (SEO), e-mail marketing, customer segmentation, loyalty and rewards programs, and overall marketing strategy.
While the vast majority of marketers understand the need for gathering and analyzing data, many still struggle with determining the best way to use that data. A recent survey showed that 45 percent of marketing executives rated their team’s use of data and analytics tools below proficient.
It’s clear many CMOs are still in the process of truly figuring out big data. One thing is certain, we know it can make us smarter. Big data is being tasked to provide a “direct measurable impact on knowing the value of budget dollars in marketing,” according to Carl Tsukahara, CMO of cloud business intelligence provider, Birst.
Aligning Data with Objectives
A Gartner study found that the top three priorities for CMOs are:
- Driving their company’s growth
- Responding to any competitive threats
- Delivering an outstanding customer experience
The question, then, is how data analytics can help marketers measure the success of their campaigns in meeting these goals. Too often, marketers view this data gathering and analysis as a passive process. They run the same campaigns and just use data to track things like hits and conversions, maybe tinkering with their strategy if certain elements are working better.
A more useful way to utilize big data is to be proactive about experimentation, trying out unique campaigns and targeting, then figuring out what works through data analytics. You want to marry human creativity that can’t be contained in raw numbers with the analytical rigor to establish which efforts need to be pursued further.
On the customer experience side of the equation, big data can be used to anticipate customer needs. You want to develop a platform that is immediately responsive to customer requests, and that means tracking user activity and feedback on your site in order to determine their primary needs.
Getting to the Core Metrics
CMOs need to determine how to make the transition from big data to useful data. Often, marketing teams get so overwhelmed with the sheer volume of data they receive from CRMs, databases, market research and other sources that they end up losing the forest for the trees.
The key step for marketers is to figure out which metrics are essential to their brand, and which are merely interesting factoids. That means determining which metrics are most closely correlated with key brand objectives such as sales growth, market share and customer retention.
According to Azita Martin, CMO of big data analytics and visualization company, Datameer, essential data metrics are those that clearly identify what gets prospects to convert to customers, and identifies which campaigns have had the most impact on customer acquisition. On the brand awareness side, brand mentions and search, media impressions, social media mentions, and number of social media followers are essential metrics to understanding customer interaction.
“Nice-to-have” metrics, on the other hand, while important for understanding the overall health of marketing, are less immediate. “Those metrics which are more the ‘canary in the coal’ mine ones,” explains Wynn White, CMO of converged data specialists, Druva. “You want to track them because they show trends in the business that when take a dip (or spike) means something is probably not working the way it is supposed to and gives you an area of focus in which to drill into,” White concludes.
The most obvious example of the kind of data points that might not have much of an impact on sales are things like Twitter followers, Facebook likes, etc. If you’re increasing your followers but not growing sales, then those followers aren’t doing you any good. Find the metrics that are essential to your business, have tangible links to your key objectives, and experiment with ways to improve those metrics.
The Human Element
People sometimes bemoan how the increased volume of data in all walks of life seems to hide people behind statistics, but the truth is exactly the opposite. Data is a way to understand people and it requires an investment in your own human capital to understand.
A recent Adobe survey of marketing professionals found that many companies lack the analytical skills to properly make use of their data. Machines can gather data, but it takes people with analytical and creative minds to turn all those numbers into actionable insights. “The job market has not caught up to the reality of this role, nor has the marketing community in general,” explains Jason Rose, SVP Marketing at human data platform, DataSift.
That’s why employment growth for statisticians is expected to significantly outpace the overall labor market over the next decade. In addition to investing in their own people, marketers need to think of data as a way to understand their customers as people. The end goal of data analytics is to be able to respond to individual needs.
Reflecting on his own recent hiring experience trying to find a qualified marketing analyst, Rose advises, “I would consider not including marketing in the job spec and finding a general “kick-butt” analyst who can crunch numbers.”
And those numbers may be getting more and more finite, as executives have gone so far as to say that big data means customer segmentation will become irrelevant. Businesses will eventually need to understand each customer as an individual, some predict.
“Marketers will say my job has always been to understand customers segments,” says IBM CEO Ginni Rommetty. “The shift is to go from the segment to the individual. It spells the death of the average customer.”
How Can CMOs Make Sense of Big Data?
Datasift Expands Its Reach With New Pulsar Deal To Make Facebook Topic Data Bigger
Datasift, which has raised a total of $77.9 million to date, is partnering with social analytics platform Pulsar to make anonymized Facebook topic data available to any brands, government, charities and businesses. Last year Datasift did a Secondary Market raise of $6.2M from Upfront Ventures. This new deal shows Datasift is pushing hard to become a mainstay of the ad agency world.
Because Datasift is the exclusive provider of Facebook topic data, this new partnership with Pulsar means businesses can access Facebook topic data and conduct research through social media. What this means is that means that the realm of social data just got bigger. The whole area is now coming into its own as agencies will be able to add it to their bank of knowledge on how social media can prove its ROI in an advertising and marketing driven online world.
So why is Facebook topic data important? Well, it anonymously shows marketers what content audiences are sharing on topics which are relevant to their brands, plus the demographics of the people engaging around them on the world’s largest social platform (remember, this is about 1.44 billion MAUs). There are over 60 ‘targets’ to sample data against.
This partnership provides Pulsar’s clients with access to anonymous and aggregated content data about the activities, events, brands and topics people are sharing on Facebook, via Datasift’s platform. Pulsar’s social analytics platform lets companies map brand audiences, assess how content spreads and engage with people on social media.
The caveat to this deal however is that Facebook topic data is a different proposition to other sources of social data and agencies and platforms still have to work get used to using them. It is to be hoped that Pulsar can make this process easier, because it’s still possible to use all this data in quite a naïve manner. It still requires thought, experimentation and planning by agencies and their brands. So it’s not a magic bullet, but it is a potentially powerful one, if used wisely.
That said, Pulsar has got to market early with this integration with Datasift, so it’s ‘ahead of the pack’ compared to its competitors.
• Nick Halstead will be speaking at the upcoming Europas Conference, which is partnering with TechCrunch.
Datasift Expands Its Reach With New Pulsar Deal To Make Facebook Topic Data Bigger
Biggest-Ever Data Breach: 3 Charged
1 Billion Email Addresses Allegedly Stolen
By Mathew J. Schwartz, March 9, 2015.
The U.S. Justice Department says three men have been charged in connection with what they say is the biggest-ever email address breach. The incident allegedly resulted in the theft of more than 1 billion email addresses from more than 100 different businesses and left at least 60 million consumers at risk from follow-on spam and phishing attacks. Two of the men who have been charged are now in U.S. custody, but one remains at large.
See Also: Mobile Deposits & Fraud: Managing the Risk
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As part of the case, two Vietnamese citizens – Viet Quoc Nguyen (a.k.a. Vandehiu, Peter Nguyen), 28, and Giang Hoang Vu (a.k.a. Lee Vu), 25, who were both residing in the Netherlands – have been charged with hacking into U.S. email service providers. In addition, Montreal-based Canadian David-Manuel Santos Da Silva (a.k.a. Jake, Lusitano), 33, was charged with helping the two men knowingly convert stolen email addresses into $2 million in profits via his affiliate-marketing company, called 21 Celsius, which operated a site called Marketbay.com.
“These men – operating from Vietnam, the Netherlands, and Canada – are accused of carrying out the largest data breach of names and email addresses in the history of the Internet,” says Assistant Attorney General Leslie R. Caldwell. “The defendants allegedly made millions of dollars by stealing over a billion email addresses from email service providers.”
Nguyen was allegedly behind data breaches at multiple email service providers, including Epsilon Data Management, an online marketing unit of Alliance Data Systems Corp. The company notified customers in April 2011 that it had detected a network intrusion the previous month that had exposed confidential data, including email addresses for customers of such banks as Capital One, Chase, Citi, U.S. Bank and Visa, as well as customers of businesses ranging from Kroger and Marriott International to Verizon and Walgreens. Ultimately, email addresses from more than 100 companies and brands were reportedly exposed by the breach.
According to a 29-count indictment against Nguyen and Vu, which was filed in 2012 and only fully unsealed last week, Nguyen – who’s described as a “computer hacker” – targeted at least eight ESPs via phishing attacks from February 2009 until June 2012. When employees at the targeted ESPs opened the messages, their PCs were potentially infected with malware that created a backdoor on the system, allegedly allowing Nguyen to gain direct, unauthorized access to the system and download any customer data being stored there. In other cases, authorities say that the phishing attacks resulted in a keylogger being installed, which intercepted account log-in information and routed it to the attackers. In some cases, the court documents say, Nguyen commandeered the hacked ESPs’ systems to launch follow-on phishing attacks against other ESPs.
Affiliate Marketing Scheme
Nguyen used tens of millions of stolen email addresses in email marketing campaigns that were designed to direct recipients to sites with which he was associated, according to court documents. “Nguyen was paid by an affiliate-marketing company a percentage of all sales completed through those websites, thereby obtaining money from the unauthorized email campaigns,” the court documents allege.
Vu has been charged with helping Nguyen by sending unauthorized email campaigns, as well as producing related artwork and helping to build affiliate-marketing websites.
Biggest-Ever Data Breach: 3 Charged
Canadian charged in one of largest data breaches in US history
A Canadian has been charged after computer hackers stole a whopping one billion email addresses from U.S. marketing companies in what authorities described Friday as one of the largest digital data breaches in history.
Three people were indicted on federal charges in what U.S. Assistant Attorney General Leslie Caldwell called “the largest data breach of names and email addresses in the history of the Internet.”
One of the accused is David-Manuel Santos Da Silva, 33, of Montreal. He is charged with taking part in a money-laundering conspiracy that allegedly netted $2 million between May 2009 and October 2011.
Prosecutors allege he entered into a marketing agreement with the other two men charged that enabled them to profit from sales generated by the spam emails.
The other men are Viet Quoc Nguyen, 28, and Giang Hoang Vu, 25, who are both citizens of Vietnam.
Vu pleaded guilty to a single count of conspiracy to commit computer fraud before a federal judge last month. He has not been sentenced.
Nguyen has been indicted on 29 counts including charges of wire fraud and computer fraud.
He remains a fugitive.
Unsealed documents from the U.S. Justice Department allege Da Silva used his Montreal-based company 21 Celsius, which ran a website called Marketbay.com, to “promote Nguyen’s hacking and spamming activities by providing him with a platform, through Marketbay.com.”
“Da Silva allegedly knew that Nguyen was spamming to stolen email addresses in order to direct high volumes of internet traffic to his affiliate marketing websites with Marketbay.com,” read a news release from the U.S Attorney’s Office.
The Justice Department documents describe Da Silva as a co-owner, president and a director of 21 Celsius.
U.S. authorities say Da Silva was indicted by a federal grand jury Wednesday for conspiracy to commit money laundering with Nguyen and others.
He was arrested at Fort Lauderdale International Airport in Florida on Feb. 12 and was scheduled to be arraigned in an Atlanta courtroom on Friday.
Calls to 21 Celsius, were not returned Friday.
Authorities said the case is significant because of the scale of the information stolen.
Acting U.S. Attorney John Horn said hackers targeted marketing companies that send bulk emails to customers of their commercial clients. They gained access to the firms’ computer systems by sending emails with hidden malware to the marketing companies’ employees.
The hackers not only stole hundreds of millions of email addresses, Horn said, but also succeeded in using the marketing firms’ own systems to send the hackers’ spam messages.
The case is being prosecuted in Georgia because that’s where computer servers were located for two of the marketing firms that were hacked. Nguyen and Vu were indicted in October 2012 but those charges were sealed from public view until after the case against Da Silva was filed Wednesday.
Canadian charged in one of largest data breaches in US history
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