by Fronetics | Oct 26, 2016 | Big Data, Blog, Content Marketing, Data/Analytics, Marketing
Big-data insights can help you segment your email database to better target prospects based on where they are in the buyers’ journey.
Most companies these days are swimming in a sea of big data, the great swaths of information they’ve amassed from sales records, social media connections, website leads and contacts, and online analytics.
At first glance it’s a tangle of information that is hard to organize and even harder to learn anything from. That’s a stumbling block that forward-looking businesses need to overcome. Big data can help breathe new life into one of the most reliable yet shopworn tools of the trade: email campaigns.
Embrace Big Data
A study by the executive head-hunting firm Spencer Stuart surveyed 171 companies regarding big-data usage. Just a little over half of the companies used their big data to help guide email, SEO, and SMS marketing campaigns. That’s a fairly low rate, given the potential leg-up that big data can provide.
Consider what Walmart is doing. The company has big-data information on about 60% of all Americans, with which it micro-targets customers based on their individual interests and habits. It’s a powerful strategy that is spreading quickly to businesses of all sizes.
How can you use big data to freshen up your email campaigns?
Be a Collector, Not a Hoarder
Chances are, you are obtaining a lot of data, especially if you have an active content marketing plan in place. Not all of the data you get is equally important. Your focus should be on data that can lead to an actionable and quick response — for example, are you gathering information on your customers’ buying habits? Do you know who they are, where they are, what their interests are, what their email address is, and how your business connects with them?
Collect that relevant data and study it. Much of it will come from the buyer’s journey — the breadcrumbs that potential buyers leave for you in your big data. These pieces of information are keys to your personalized email responses.
Respond In Kind
Most experts agree that a quick and targeted email response is a good strategy for encouraging a new customer to make a purchase. The email needs to respond directly to the buyer’s interests — using information you’ve (hopefully) logged with your big data.
From this point on, it’s crucial to make sure that every email that is sent to that buyer is built around a backbone of big data. Nurture your customers with personalized emails that offer content and deals that line up with their specific interests.
Don’t Mess with the Masses
Mass emails — the generic sales pitch email — used to be the cost-effective and simple way of reaching and converting customers. Now, it’s more than likely they’ll get sent to the trash, or worse, the spam filter. The mass email is your one-way ticket to spam purgatory.
“Traditional methods of mass marketing doesn’t resonate anymore and they’re being ignored by the audience,” said Volker Hildebrand, Global Vice President of Strategy at SAP Hybris, in a recent interview with Forbes. “Data is the fuel for customer engagement, and being able to pull together all the relevant information about in real-time.”
You can do better than the mass email approach. If you’ve collected relevant data and you’ve studied your buyers’ journeys, you have the tools in place to build a smart email campaign. Tailor your campaign to personalize your approach to your customers, and more than likely they’ll open that email.
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by Fronetics | Jun 9, 2016 | Blog, Content Marketing, Marketing, Strategy
A data-driven content marketing strategy will increase your program’s success and help win the buy-in of executives.
What is driving your digital and content marketing strategy? If all you have in the driver’s seat are a few creative ideas, you may find yourself frustrated with the results and struggling to garner support from the C-Suite.
Different audiences respond in different ways. The question is, where are your potential new customers and what are they looking for? Data plays a critical role in uncovering those answers.
Data can guide you to:
- Define your target audience. Who are you trying to reach? When can you best reach them?
- Select the best topics for your content. What information do they need, and what will peak their interest? What do they seek most from the content they read?
- Narrow down a distribution strategy that will produce results. Which digital and social media channels will best reach your audience, grow your business, increase sales, and improve your brand’s reach? Which networks are your competitors using most?
- Gauge what is working and what is not. Reportedly, 53% of digital content marketers don’t measure their success. No wonder so many content marketing programs fail. If you don’t take the time to determine what content is resonating with your target audience, how will you know what to produce in the future?
- Tune into market changes. As your business evolves and customers’ needs change, data serves as your compass to remain competitive in an ever-changing marketplace.
A data-driven strategy will win over the C-suite
In addition to giving you a foundation for your strategy, data can garner the support of the C-suite, which you must have in order to fund your marketing program. A plan based simply on ideas, no matter how brilliant, will not appeal to executives who base decisions on data.
They want to see how your marketing plan provides answers to the needs of your target audience (potential customers) and what those customers are worth to the company’s growth and success. If your strategy aligns with data, they’ll be able to get behind every point.
Creating a data-driven strategy
Aligning your strategy with data takes some time and effort, but it is crucial to optimizing the performance of your content marketing program and winning C-suite support. Here are some steps to get started.
- Analyze your reports, data, and interviews with stakeholders in the company about your target customer. Compile this information, and document the very specific demographic(s) you want to reach. Research the digital behaviors and patterns of this demographic.
- Audit your existing content (or hire an expert to do it). Look at the substance, source, and performance of your most successful and your least successful assets. Are there changes you can make to your poor-performing content to improve it, based on learnings from your successful content and your audience research?
- Plan an editorial calendar of future content based on what has been successful in the past. Sharing this information and seeking ideas from employees outside the marketing department can be a very valuable exercise.
- Test the distribution channels and times that have been most successful in the past and that fit the behaviors of your target audience. Continually refine your distribution strategy based on your results.
- Don’t forget to document your strategy! Marketers who put it in writing report success at significantly higher rates than those who don’t document their strategies.
By distributing the right content, at the right time, to the right audience, on the right channels, your content marketing program will reach its maximum potential.
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by Elizabeth Hines | May 11, 2016 | Blog, Strategy, Supply Chain
If Seneca the Elder could have peered into the future, shock is likely too weak of a word to describe his reaction. The Roman rhetorician is credited for being among the first to complain about the overload of information when he, in the 1st century AD, lamented that the abundance of books had become a “distraction.”
Around 1440 AD, another round of complaints erupted with the invention of the printing press. Overwhelmed by the sheer amount of new information, scholars of the Gutenberg era found the proliferation of printed materials too difficult to manage.
Fast-forward a few centuries and you find articles titled “Death by Information Overload.” Published in 2009 by Harvard Business Review, the article makes a case that we’ve heard countless times over the past few years: We are drowning in a flood of data.
However, the writer, Paul Hemp, also makes a point that I want to focus on:
There’s hope, though. Innovative tools and techniques promise relief for those of us struggling with information inundation. Some are technological solutions—software that automatically sorts and prioritizes incoming e-mail, for instance—designed to regulate or divert the deluge. Others prevent people from drowning by getting them to change the way they behave and think. Who knows: Maybe someday even I will enjoy swimming in the powerful currents of information that now threaten to pull me under.
Nearly two years ago, I argued in this space that vendors would be wise to spend less time on their sales pitch and more time presenting data in a digestible format, ensuring compatibility with the end-user’s legacy systems, and aligning the solution with the end-user’s key performance indicators (KPIs).
Few people actually object to the value of data, and most are well informed of its potential impact, according to several surveys. Collected in a warehouse environment, data can profoundly boost productivity, safety, and inventory accuracy.
The issue that many still need to address is that all too often the step from collecting data to letting it drive decisions is more than the average organization can handle. Surveys show a surprising number of companies report they are either wary of advanced analytics tools or have failed to leverage the technology. Data generated by sensor-enabled technology, for example, does little good unless the end-user knows how to interpret and act on it.
But there are signs vendors are responding to the demand for user-friendly data. Just as you do not expect to sort through masses of data to find out how fast you are driving, leading vendors are eliminating and simplifying steps to help end users get the information that they are looking for without time-consuming analysis. New widgets or apps designed to consolidate data coming off multiple sensors will make data collection in the warehouse more accessible, and, as a result, more likely to lead to operational improvements.
Then talk of data overload may quiet down — until the next wave of disruptive innovation hits, that is.
What signs, if any, have you seen of more user-friendly data?
This article originally appeared in EBN Online.
by Elizabeth Hines | Sep 1, 2015 | Big Data, Blog, Data/Analytics, Strategy, Supply Chain
Many organizations that jumped on the big data bandwagon have struggled to turn their new, boundless collection of data into actionable business information. As consultant Rich Sherman of Athena IT Solutions puts it, today’s businesses are struggling with “the transformation of data into information that is comprehensive, consistent, correct and current.”
Enter data governance programs, and, consequently, the data steward. Technology cannot always extract the most useful data, but the data stewards can, meaning the success of the data governance program rests to a large degree on their shoulders. But data stewards can be viewed with suspicion by other employees and nothing can kill the spirit of hard work more than distrust or a feeling that management is snooping and ready to pounce at the sign of even the slightest misstep.
Some business users are under the impression data stewards have been tasked to play dual roles, championing the organization’s data governance program while also using their position to crack down on anyone stepping out of line. To some, the data steward is really a data cop who “police” rather than manage the organization’s critical data elements. They believe anyone can be caught in the net cast by the data stewards as they fish for out-of-compliance data and bring it into line with policy or regulatory obligations. This can create needless friction within the organization and threaten the effectiveness of data efforts altogether. We can’t ignore concerns caused by the growing presence of data stewards at many organizations; in fact, it makes it even more important to show why such concerns are generally unfounded.
While it is true data stewards are indeed tasked with ensuring compliance with the policies and processes of the data governance program, critics need to bear the end goal in mind – to turn massive amounts of data into a useable corporate asset. And data stewards themselves can actually play a role in the effort to help “to take the view of data governance from police action to harmonious collaboration,” as another expert, Anne Marie Smith of Alabama Yankee Systems, LLC, put it. It won’t hurt for the data stewards – or the data governance managers – to acknowledge some employees will initially question their intentions. However, by reaching out to each business unit and explaining how data governance works and why improved data management will benefit the organization, the distrust can dissipate. Similarly, if the data steward is recruited from within the organization, it will alleviate some concerns since business users are more likely to trust a familiar face.
The complexity of data governance comes with a host of pitfalls – fears of data cops shouldn’t be one of them. What’s been your experience with data stewards in the supply chain? Do they play an important role in your organization?
by Fronetics | Dec 17, 2014 | Big Data, Blog, Data/Analytics, Internet of Things
The Internet of Things (IoT) is ubiquitous. Because of this it can seem abstruse. Puneet Mehta does a great job of putting the concept in layman’s terms: “[A] plethora of “dumb” objects becom[ing] connected, sending signals to each other and alerts to our phones, and creating mounds of “little data” on all of us that will make marketers salivate.”
The mounds of data created by the advent of the IoT does not just make marketers salivate. Gartner predicts that the IoT will add $1.9 trillion in value to the economy by 2020. Looking ahead, Cisco estimates that the IoT will create over $14 trillion in value over the next 10 years.
In 2003 there were 500 million connected devices. Cisco estimates that this number will increase to 50 billion by 2020. Morgan Stanley believes this number will be higher – it estimates there will be 75 billion IoT devices by 2020.
“Dumb” objects are becoming connected; the physical and digital worlds are converging. Mounds of data are being collected.
IoT and Big Data
Mukul Krishna, from Frost & Sullivan, presented a simple incremental view of the relationship between the IoT and big data. In short, IoT devices can be thought of as data sources. These data sources generate an incredible amount of data – much of which was previously not accessible. The information and insights from big data allow for better decision-making.
The amount of big data created each day in 2012 was 2.5 exabytes (2.5×1018). In 2014 the amount of data were created each day was 2.3 zettabytes (2.3×1021),
An IDC forecast shows that the Big Data technology and services market will grow at a 27% compound annual growth rate (CAGR) to $32.4 billion through 2017 – or at about six times the growth rate of the overall information and communication technology market.
The need for a plan
McKinsey & Company offer sage advice: put a plan in place.
The payoff from joining the big-data and advanced-analytics management revolution is no longer in doubt. The tally of successful case studies continues to build, reinforcing broader research suggesting that when companies inject data and analytics deep into their operations, they can deliver productivity and profit gains that are 5 to 6 percent higher than those of the competition. The promised land of new data-driven businesses, greater transparency into how operations actually work, better predictions, and faster testing is alluring indeed.
But that doesn’t make it any easier to get from here to there.
So how does one get from here to there?
The answer, simply put, is to develop a plan. Literally. It may sound obvious, but in our experience, the missing step for most companies is spending the time required to create a simple plan for how data, analytics, frontline tools, and people come together to create business value. The power of a plan is that it provides a common language allowing senior executives, technology professionals, data scientists, and managers to discuss where the greatest returns will come from and, more important, to select the two or three places to get started.
What impact has the IoT and big data had on your company? Does your company have a plan in place?
