Everyone’s talking about Big Data and the power it holds to transform marketing initiatives from making random guesses and hoping something sticks to strategically refining and focusing marketing strategies with laser precision. But Big Data alone doesn’t magically transform your results; true transformation lies in how you leverage data to your advantage.
For many marketers, the customer experience is a key focus. Obviously, customers that have a fantastic experience with your company keep coming back for more, and they’re also more likely to recommend your business to friends, family, and acquaintances compared to customers who have had a so-so experience.
So, how can marketers best leverage Big Data to gain valuable customer experience insights and then put those insights to work to dramatically improve customer satisfaction, boost repeat purchases, increase customer retention, and achieve the other desirable results you’re aiming for? To find out how today’s top marketers are leveraging Big Data to gain CX insights, we reached out to a panel of marketing experts and customer experience pros and asked them to weigh in on this question:
“How can marketers leverage big data for customer experience insights?”
Read on to find out what our experts had to say and learn how you can leverage Big Data to improve business outcomes.
Meet Our Panel of Marketing Experts and Customer Experience Pros:
|· Brady Keller|
· Leon Sun
|· Justin Ohanessian|
· Kim Ekin
|· Shayla Price|
· Max Page
Brady Keller is a Digital Marketing Strategist for Atlantic.Net, a trusted hosting solution for businesses seeking the best enterprise-class data centers.
“Understanding Big Data is a very important piece of creating a marketing strategy in today’s digital world…”
While data analysis has been around for a very long time, the sheer volume of big data is something that is relatively new. Marketers now have the ability to use company owned and public data to explore customer behavior, usage patterns and preferences. This information can be leveraged to find your desired new customers through automatic segmentation, customer look-alike analytics, and targeting. Reaching the right prospects is quite valuable, compared to soliciting non-targeted consumers. Another great way to leverage big data is through the use of A/B testing. Before you implement your strategy on a large scale, it’s best to test out multiple approaches.
Leon Sun is the owner of SocialLia, a resource for businesses and individuals who are interested in building their Instagram presence.
“Big Data is extremely helpful for insights related to customized promotions
and special offers…”
Since each customer is going to have their own individual preferences, personalization is key. This can have a very big impact on overall sales and profitability in the long run, not to mention customer loyalty. Leveraging big data can give businesses the tools they
need to analyze customer and market data in order to create personalized offers that are targeted to the correct audience. This customer data is especially useful for real-time insights which allows for real-time decision making.
Brennan founded two companies in the content marketing space. The first, Pandemic Labs, is a digital marketing agency that has been included among the Inc 5000 fastest growing private companies in the U.S. Brennan’s second venture, Cortex, helps companies leverage big data for customer experience insights and to improve creative content.
“To best leverage Big Data for customer experience insights…”
Marketers can gather all of the available marketing attribute data (for a photo, example attribute data points would be color, objects in the photo, size, resolution, message, etc.) about their marketing content and combine that in a database with all of the deployment data (when and where the content went live, how much it was promoted with, how large the audience was at the time of launch, etc.). Then they can cross-reference that combined data set with performance data (social media data, internal click-through or conversion data, customer experience data, etc.) to find patterns in what works and doesn’t work to drive specific experiences.
When your organization is no longer guessing about the impact your marketing changes will have on the customer experience, the strategy can be a lot more detailed and efficient.
Some of the largest brands in the world are being disrupted by smaller and nimbler organizations who have built systems themselves or bought licenses for software that does all of this gathering and analysis automatically.
Amanda Basse is the Marketing Coordinator for staySky Suites I-Drive Orlando. Amanda is passionate about leadership, self discovery and marketing. She hopes to inspire people to passionately pursue their dreams.
“Figuring out which data to track when implementing a customer experience survey is the most important part of the data collection…”
We prefer to use a 7-point scale over a 5-point scale. A 5-point scale includes a 20% variation between grades, and it is difficult to get actionable insight from a 20% gap. Going from a 7-point to a 5-point scale reduces variation by 5%, and this allows you to pinpoint where you need improvements. Also, knowing what to do with the data is important. If you are getting 85 sevens, 10 twos and 5 ones, you are much better off focusing on the feedback from the ones and twos to see where you need improvement, instead of congratulating your team on the 85 sevens.
Michael Reddy, Founder & Chief Analytics Officer of Digital Acumen, has worked with Fortune 100 companies in a variety of roles: media mix modeling, statistical modeling, test & learn, product/program/project management, process improvement, loyalty program
management, and web analytics.
“The geyser of consumer data separates today’s marketing from that of the past…”
We’ve gone from little to no data collected, to a huge amount of customer data both being collected and analyzed. In between, we started collecting more and more data but didn’t have the cost effective tools and expertise to leverage that data.
We are reaching a point where the cost of the technology to collect and store the data is met with marketers’ desire to analyze it. The abundance in new growth in data comes from the Internet of Things, social media, web data, and proprietary data collected by large organizations.
The reasons for marketers to invest in big data boil down to increasing profitable sales.
From Mckinsey, a retailer using big data to the full could increase its operating margin
by more than 60 percent. And if U.S. healthcare were to use big data creatively and effectively to drive efficiency and quality, the sector could create more than $300 billion in value every year.
To see these gains, the primarily lever is to provide a highly personalized experience for your customers.
Personalization: Every company interacts with their customers in one or more ways. For the largest omni-channel companies it includes: web, mobile, phone, chat, in person, through sales people, ordering systems, loyalty programs, etc. Every one of these channels helps you paint a more detailed picture of that customer, allowing you to personalize their user experience.
Mckinsey research suggests that personalization can deliver five to eight times the ROI on marketing spend. The main reason companies have been held back is because they weren’t able to harness all of the data (and sometimes even different data by source) that they are collecting.
In the past, it was tough given that in the example above we’re collecting both structured and unstructured data from eight distinct sources. This changes with big data technology becoming more accessible and affordable. In the personalization example above, we could learn all of these things: the customer looked at three different products and four categories, hovered over a certain promotion, responded well to a AB test on a certain call to action test, visited our physical store three times in the last month, has two kids and a wife, is in the loyalty program. As the marketer, it’s up to you to personalize the user experience using this excellent treasure trove of data.
Pratik Shah is the director of marketing at Grin, a social shoutout platform that connects brands and individuals to social influencers. He also consults with brands on marketing strategies and implementations.
“The best way to leverage Big Data for customer experience insights is…”
One way to leverage Big Data is by looking at cart abandoners. As per recent studies, the abandon cart varies between 60% – 80% depending on the industry. This is a major segment of orders lost.
Cart-abandonment data can be used and surveys can be sent out to customers to figure what isn’t working at this stage of the funnel. For high value cart abandonment, the customer service reps can call up these customers and figure out ‘what went wrong,’ allay their concerns, and even encourage them to complete their transactions.
The insights gleaned from surveys and customer rep discussions can be used to further smarten up the product and process and help with a better customer experience.
As the leader of the digital marketing and marketing technology function at the agency, Joey oversees large scale digital initiatives for clients and all day-to-day management and HR responsibilities for the digital team. He has been a leader at the Xoo for almost two years.
“Business insights can be gleaned from big data in several ways…”
A common approach we normally take with customers is mining all customer interactions and communications then classifying each interaction into a certain category. Next, analyze those categories for specific trends related to business outcomes. With a large enough data set, the trends can be considered statistically significant and can inform future marketing and sales strategy changes. For example, with one client, we’ve noticed a higher degree of cancellation several weeks after their customers inquire about an address change or update. As a result, we’ve changed the marketing strategy for that group of customers to hedge against cancellation.
Russ Klein, CEO of the American Marketing Association, and expert in marketing can give advice on how marketers can leverage big data for customer experience insights.
“Here are five tips for marketers, to help their companies generate usable, data-based insights…”
- Determine what’s actionable within the business
- Simplify the process by focusing on decisions stakeholders or customers will make
- Be mindful of stored data
- Understand consumer and business needs
- Find a data balance
William Hanson is the Head of Business Intelligence for KAX Media, a digital publisher focusing in iGaming with websites such as Gambling.com and CasinoSource.co.uk.
“There are several ways in which big data can be leveraged to gain insight on customer experience…”
In the case of our website Gambling.com, every
click – or ‘event’ – is tracked throughout the website for each individual user from the moment they enter and leave the website.
Each visitor and subsequent click performed on that website is assigned a unique User ID and Event ID, respectively, and stored within a database. Along with the initial entrance, we are also able to store which marketing channel that user arrived from, whether it be from Google, Facebook, Direct Navigation, etc.
As you can imagine, over time we are able to collect a rather extensive amount of data on how our users interact with our website. This data allows us to draw conclusions on various things about the customer’s journey such as, “Why does this landing page lead to a conversion more frequently for Facebook visitors than Twitter visitors?” or to something as simple as, “What is the first click users generally perform once initially arriving on our website?” The possibilities are endless on things you are able to analyze and thus optimize on your website leading to more conversions and increased sales.
Danyal Effendi is Digital Marketing Professional with 6+ years’ global experience. He is currently working as Digital Marketing Team Lead at PureVPN, world’s leading VPN service in SAAS industry.
“With growing digital trends, the importance of Big Data is increasing…”
And now it is impossible or extremely hard to make efficient decisions without using data. The role of big data in marketing is very critical because data gives insights on what customers want. Marketers can use big data to predict future outcomes on the basis of historical trends. The best use of data is to create a customer journey process and improve user experience. There are multiple tools that can be used to collect data as well as analyze customers’ interactions with the website and app. The insights from this big data helps in optimizing the customer experience and increasing the conversion rate. This data can also be used to increase interaction and engagement with potential customers.
Besides this, live chat data helps marketing teams learn about customer preferences and problems which they directly share with the support team. Through this data, a marketer can know what customers expect from them and what sort of problems they are facing while using their products/services. This helps us to solve their issues more efficiently and make their online experience easy and convenient.
Swapnil Bhagwat is Senior Manager – Design & Digital Media, implementing marketing, social, digital and design strategies for the group companies. He is an MBA graduate with work experience in the U.S., U.K., and Europe. Swapnil has worked for more than a decade across a range of businesses for the global markets.
“In today’s data-driven ecosystem, marketers are heavily dependent on precise information more than ever before…”
To gain actionable insights about their customers. Be it the right price to drive sales, or product features that would attract customers, it’s big data that can help them to make critical business decisions. By putting big data to the right use, marketers can extract valuable analytical insights to maximize the customer experience.
Sean Martin is the Marketing Manager at Directive Consulting. They publish thought leadership in Moz, PPC Hero, Wordstream, Sitepoint, Crazy Egg, and other industry leading sites. The Directive Consulting team also speaks at State of Search, SMXwest, Digital Summit, and are recommended by Moz, Unbounce, Google, and Bing.
“Today, a high-quality user experience of your site is almost the norm…”
The truth is that in today’s supersaturated market if you don’t have a solid UX on your site, you aren’t even getting to the table. So, going into the future, what will separate the great companies from the good will be their ability to nuance their big data to really give them powerful insights on small changes to their design. The segmentation input based, little things are going to be the demarcators of success in 2017.
Justin Ohanessian is a Growth Specialist at Sticky.
“One useful way to leverage Big Data for customer experience insights is…”
Eye tracking has traditionally been used in market research, but now it’s more accessible and affordable than ever. Eye tracking data can help marketers measure how engaging their creative is by knowing if it’s seen and for how long.
Bryan is the CEO of GreenPal which is best described as Uber for Lawn Care.
“Sometimes Big Data sources can be right at your fingertips…”
We leverage our data, combined with publicly available census data, for marketing insights.
For example, in a recent campaign we ran in Nashville, TN, we ran a pay-per-click (PPC) Adwords campaign with one ad targeting the entire metro Nashville area. The headline read ‘Local Lawn Pros in Nashville are a click away,’ and I thought the performance of the ad was good with a click through rate of over one percent and conversion rate of over 10 percent on the Nashville landing page, but we needed to improve on it.
We thought, “How can we make this more contextual and relevant to the viewer?” So we researched census data, looking at the average income and home values throughout the Nashville area.
We found that East Nashville, an up-and-coming neighborhood, was populated with more working class residents and a creative class demographic, and we hypothesized this customer segment would be price-sensitive but still not want to cut their own lawns. So we segmented those zip codes and only ran a specific ad for them, with a headline ‘The Cheapest Lawn Mowing in Nashville. Lawn mowing from $20.’
We then created a matching landing page. After running the ad for one month, on-page analytics proved the guess to be true. We saw more than 200 percent lift in click through rate and 30 percent lift in on-page conversion.
Studying the data your own business generates can tell you which of your online marketing campaigns works best. Do the ads appeal to your target market or another market altogether? The data may also point to completely new areas of customer interest.
Grace Garvey is the Content Marketing Manager for TinderPoint.
“The beauty of big data is it can provide marketers, specifically content marketers, with vast amounts of potentially great content…”
And rigorous information is always valuable to digital marketers.
Customers are the primary focus of content marketing. We need to understand our customers and have an optimal customer profile or persona in mind when creating content. We need to know their preferences – some big data vendors specialize in detecting customer emotions – and their patterns. Big data techniques facilitate advanced customer segmentation.
Omni-channel marketing aspires to provide customers with a seamless experience, regardless of channel or device. Big data helps achieve this by putting all data sources under a single umbrella. When departmental siloes are eliminated, it becomes possible to consolidate and integrate company data to get a comprehensive view of the business. This also helps the business internally, leading to better communication between employees and departments, with the customer reaping the benefit.
Marketers are becoming increasingly savvy about the best ways to use big data without being invasive. The ability to measure customer response in real time as well as measuring individual campaigns means they have enough data to tailor offers by channel.
Customer data, specifically customer insights, can inform content and enable better targeted campaigns. It also allows you to measure content marketing campaigns more accurately, and helps with the personalization and creation of tailored, smart content. Correlations between the fast-evolving worlds of big data and content marketing continue to unfold, delighting your customers and improving your bottom line.
Phill Thompson is the Sr. Marketing Strategist at Walk West, a digital-first marketing agency in Raleigh, NC.
“Big Data is often misunderstood or unclear…”
What it is, how to act on it, etc. are mysteries for many. As marketers, we use it to find out what customers want by looking at what they’ve done in the past. From social media sentiment to purchase history, it’s our job to listen, analyze, and respond. What are they telling us? They’re sharing pain points, desires, positive and negative sentiment, and their future expectations. We can now develop a 360-degree snapshot of customers, which gives us numerous clues about how to improve their experience. How we approach data is dependent on factors such as our industry and company-specific, strategic marketing goals. And there are numerous ways to enhance customer experience using big data. Below are a couple of broad examples that cut across industries:
- Knowing customer touch points and making tailored offers based on that insight. Utilizing our knowledge of the buyer’s journey (awareness, consideration, decision), we can make the right offer at the right time.
- Improving your website user experience. Reviewing website analytics data — using Google, HubSpot, or other tools, for example — is easier these days to identify customer pain points and better help them get information or make decisions. This is a high value way of digitally bringing your strategic business goals in line with your customers’ needs.
Adelyn Zhou is a marketing and technology leader who has worked with companies such as Amazon, Nextdoor, Eventbrite, and Oscar Health. Zhou is the CMO at TOPBOTS, a leading research firm focused on the strategy, design and marketing of AI and bot technologies. She has been featured in VentureBeat, Forbes, Wired, etc.
“Companies can use artificial intelligence to find trends in their existing customer service…”
For example, big data insights can help companies anticipate an increase of product demand. If there is a demand spike for a certain product in the Northeast, even though the total order volumes may be low, big data can identify this and use it as an indication of an upcoming trend. This mapping will help teams order more of the inventory and for CE teams to get ramped up on this popular product.
Kim is head of marketing operations at Presence Marketing and analyzes a lot of data to deliver SEO results.
“When it comes to big data, the most important thing is the analytics…”
Without a good analyst, you’ll miss trends and patterns that could have led to a great return. The best way to collect data is to err on the side of too much, rather than not enough. I was contacted by a well-established business that had a great idea for email marketing to their warm leads and customers – and then brought out a drawer of business cards. They had neglected to collect email addresses, instead focusing on home addresses and phone numbers, because they always had. Had they added an email section to their data collecting, it would have been much more cost-effective to get their email marketing list up to speed and ready to market to, which would have provided genuine insights showing how their customers consumed their content. As it stands, they ended up sticking to posting out flyers – more expensive and a lower conversion rate + little analysis potential = not a great campaign. This case shows that collecting relevant data would have saved a lot of time and money, and they missed many insights that would have helped to gain business in the future.
Zhe (Haley) Gong, digital marketer at Webpower Asia, discovered her passion for online communication when she studied at the Johns Hopkins University in the U.S. Now, Haley, together with her team in Shanghai, strives to provide marketing automation solutions to international companies wishing to reach and engage their audiences in China.
“Marketers can leverage Big Data for customer experience insights by…”
Based on a customer’s personal information (e.g., size of shoes and favorite color), companies can predict what type of products fit for the person and send out promotional messages accordingly. Similarly, based on one’s shopping history, companies can up-sell or cross-sell supplementary products to this person or send out maintenance notifications to remind the customer to bring the product back for inspection or recommended maintenance. Furthermore, with Social CRM, companies can make themselves more relevant by using data from customers’ networks. For example, if you see quite a few people in one’s network has purchased a product, then it’s good to also recommend the same product to this person.
By collecting data from social media (e.g., through the ‘check-in’ function and in-app location tracking), you are able to know the real-time location of a person. Based on this information, companies can push notifications about nearby stores or promotions that are happening around the customer.
Haris Mumtaz is currently associated with one of the leading VPN service providers in the industry, PureVPN, as a Brand Strategist. Apart from being an online security activist, he also keeps an eye on the latest marketing trends in the industry. When he’s not at work, he loves to go on adventurous trips with music as his sole companion.
“Big Data, once filtered and structured, can prove to be extremely beneficial for marketers…”
It can tell how a customer interacts with your website and product. This shows what kind of people your visitors and customers are.
Marketers can then plan campaigns according to the identified behavior of users gained from the data. Targeted campaigns can also be planned.
New use cases of a product can also be figured out, which will help marketers to market their product to a new audience with a new perspective.
Tom Feltham is the Marketing Director at Discover CRM. Tom leads company marketing initiatives including lead generation, product development, advertising strategy and email marketing.
“The biggest challenge for marketers looking to leverage Big Data is…”
How they process and analyze the large customer datasets available to them. The danger lies in drawing inaccurate conclusions about how your customers’ behavior and demographics influence their value to the business.
With that in mind, it is crucial that marketers dust off those statistics textbooks and start considering which correlation coefficient they are going to use, how statistically significant is a correlation, and whether there is a causal relationship between datasets. Only then can they start to act on the customer data in front of them.
Dejan is the Chief Technical Officer of Concentric. He is currently leading the development of Concentric Market, a market simulator. Dejan is an expert in the fields of artificial intelligence and simulation of social behavior. Over the past couple of decades, Dejan has engineered decision support software to help companies around the world make better decisions faster.
“Marketers are increasingly using Big Data to understand the customer experience and bring new sources of growth to their organizations…”
Most of these endeavors, however, are confined to backwards-looking analysis. A few innovators, like teams at Microsoft, Toyota, and Whirlpool, are moving into the realm of forecasting consumer behavior. They apply the scientific method on top of their big data capabilities to reach a far greater value. They re-allocate their resources away from initiatives that may have worked last year, but will not work this year. They conduct experiments within the market and learn orders of magnitude faster than their competitors. And they act with a confidence not previously seen among the marketing community.
Billions of dollars each year go to analytics companies, consultants, data scientists, and statisticians. The insights they generate fit one of two categories: descriptive or evaluating. Descriptive insights are in the form of dashboards, visualizations, presentations, and reports that do little more than distill the historical trends of the consumer experience or any other metric of interest. Evaluation insights are using some form of statistical analysis to infer how much of a given outcome is attributed to various levers the marketer can pull. Both are forms of summarizing what has already occurred. None deal with what happens next. And that is where the greatest value for the marketer lies: in the ability to forecast and learn over time.
The only way to get to reliable forecasts and learning in human history has been to apply the scientific method. Soothsayers and oracles over the centuries have attempted other methods, but to no great result. So, in marketing too, it is only a matter of time before marketers unlock the power of scientific forecasting and learning.
Let me share an example. Say that the marketer wants to understand what factors of consumer experience they need to improve to increase repeated customers. Instead of using big data to mine for statistical insights, analysts could employ a two-step process. First, they would hypothesize (form theories) about how people make decisions, change their perceptions, and are influenced by marketing. These theories will produce forecasts of
what is likely to happen given certain future conditions. Next, the analysts would use all data they have (and continue to acquire) to compare their forecasts to what actually happens. Every time they are off they have a chance to improve their theories. Theories and forecasts will improve through cycles of learning. It may take time, it may lead to dead ends, but whoever cracks the case, will have a great power: the ability to reliably forecast human behavior and to know how to influence it.
This type of scientific approach was not possible before the advent of big data (and tiny processors) as there was not enough granularity and volume of observation to learn quickly (and not enough computing power). So, today, some marketers are ready to move from big data as a source of descriptive and backward looking to big data as scientific and forecasting. Some of these marketers are Concentric’s early adopters. We see it every
day that the greatest value of big data is yet to come.
Shep Hyken is a customer service expert, keynote speaker and New York Times bestselling business author.
“The increase in the ability to mine data…”
From different sources and the ease in obtaining it can be a game-changer for any company that figures out how to use it properly; which is to give the customer a better experience. That experience can tie to a better customer service experience as well as a better buying experience.
Social media channels provide data on your customers’ likes, dislikes, interests, occupations, and much more. If I make a social media post on my birthday, that information becomes important data that someone or some company can use. If I show pictures of my dog on Facebook, my love for man’s best friend becomes part of my profile.
So the question is what data is important and will help improve your customers’ experience? Is it weather, economic, buying patterns, social media postings, online buying behaviors or something else? Once you have this information, how do you exploit it? Here is the point of all of this: Data is worthless unless you have the right data and then do something with it.
Shayla Price creates and promotes content. She lives at the intersection of digital marketing, technology, and social responsibility. Originally from Louisiana, Shayla champions access to remote work opportunities.
“Big Data is an opportunity to personalize the customer experience…”
Use data to deliver customized product selections, one-of-a-kind loyalty programs, and proactive customer service.
Big data isn’t about saying your customer’s name in an email. Instead, data is an enhancement tool to show customers your brand truly understands their needs.
Jessica Thiele is the marketing manager at VL, a Canadian SaaS data integration service provider.
“To leverage Big Data for customer experience insights, marketers should…”
Expand your thinking – your business is an ecosystem of data. Marketers are faced with an exponentially increasing challenge: more data from more applications on even more customer behaviors. And they can’t possibly extrapolate any insight from any of it if they’re thinking about a single application (or platform) at a time – it’s like looking at a puzzle with most of the pieces missing.
Leveraging your business’ data for marketing efforts starts with thinking of all the data your company has, even beyond the typical suite of marketing automation platforms and social media outlets. It’s about getting a complete picture of your business and consumers as possible, from top to bottom. This means thinking about all the applications in your business as a single ecosystem; together, these applications form who your business is to the consumer. Once all the applications are integrated together so that all your company’s data is where it needs to be in all applications in near real-time, then you can start to better understand the customer experience from all directions (and not just from your marketing automation software).
Keval Baxi is a die-hard entrepreneur. In 2007, he joined his first company BaxiTech.com; a network consulting agency focused on Microsoft & Cisco powered networks. After being acquired by CMScentral.net, Keval now is the Chief Executive Officer and President of the board at Codal, a global digital intelligence consultancy focused on cloud, web and mobile development. Keval has experience from a BS in Entrepreneurship/Management from the DePaul University, Chicago.
“Having access to Big Data is slowly transforming what it means to be a marketing professional in 2017…”
Ultimately, big data allows the marketer to more accurately target their prospective clients, be more personal, and deepen customer loyalty. There are tons of marketing dollars being spent across enterprises across the world, and data is what allows the marketer to know which dollars being spent are the most efficient. Big data can improve any customer experience by allowing that customer to receive personalized, relative and targeted promotions, instead of promotions that are meaningless.
Renee Tarnutzer is a Product Marketing Specialist at Understory, Inc., weather hardware and analytics company delivering hyper-local, ground-truth data. Tarnutzer transforms digital marketing strategies into profitable realities through user experience and engagement, email marketing, A/B testing, SEO and SEM all the while reviewing analytics to ensure data supports every move.
“One of the ways that marketers can leverage Big Data for customer experience insights is…”
To understand the customer journey during a weather-driven micro-moment. By uncovering critical, emotional micro-moments, marketers can provide relevant messages to their customers immediately before and (where applicable, during) a weather event when they are in an “I want to know” moment. This can also be done after a weather event when a customer is in an “I want to buy” moment. For instance, before a storm, marketers can leverage weather data to build loyalty by offering customer preparedness tips like how to prepare for a flood. After the storm, marketers can leverage address-specific weather data to know which customers have been impacted by a weather event. Marketers can help customers with tips like how to remove a fallen tree to letting customers know you have supplies on hand to help them recover and return to normalcy. Marketers can also leverage weather data during seasonal changes when customers are either more likely to get out and about or are getting prepared to hibernate for the winter.
Sunil Thomas is CEO of mobile engagement and analytics technology provider CleverTap, a company he cofounded to help app developers to better use their data to create more personalized experiences across devices and platform.
“There’s so much buzz about data-driven decision making that Big Data has become overwhelming…”
Every day, businesses collect massive amounts of data. While technology to store and access it has become better and faster, all we’ve really done is develop a prevailing mentality that says, “When in doubt, collect it, store it and figure out what to do with it later.” And so we collect more.
What we need is to take a step back and remember is that data itself is useless. Collecting more of something that’s useless doesn’t help anything.
The question we need to address is how we turn big data into smart data – data that we can adequately analyze and understand.
Thankfully, there are rapidly-evolving technologies that will support the big-to-smart transformation such as machine learning, artificial intelligence, and even new data modeling algorithms. Still, most businesses don’t have the luxury of time to wait. For now, we need to stop the insane data collection and instead go back to basics.
First, remember why you’re collecting data – you’re looking to gain insights that will help build solutions that address problems. The smart approach is to prioritize those problems, then narrow your big data down so you’re just dealing with the subset that correlates to that problem. Then, with a more manageable data set, make hypotheses and run experiments until you find your solution. Now, you’ve made your big data smart data.
Vaclav Vincalek is a serial entrepreneur in information technology, Big Data, and social media. He’s the CTO of Get Lucky Hotels and serves on the board of directors and in executive leadership roles at several other companies.
“We are starting with the assumption that the marketer has access to data…”
To truly capture the customer experience, the data gathering has to happen through the whole organization. You can’t have big data for the marketing team, another set for sales, product or support. Properly (data) mapping the whole experience which the customer has with the organization provides the opportunity to custom-tailor the interaction from a unique value proposition to buying experience and any customer support. Part of the ‘big data’ endeavour should be also Predictive Analytics. This allows you to anticipate customer needs and requirements, and ultimately leads to higher customer satisfaction.
Tabitha Jean Naylor is the Founder of Successful Startup 101, a digital magazine that provides answers to today’s most pertinent questions facing startup founders, and the Owner of TabithaNaylor.com, a marketing firm that delivers ‘big agency’ quality at rates that are affordable for startups and small businesses.
“Big Data has become kind of the trending ‘thing’ lately, and it’s easy to see why…”
With big data, you are getting specific information on your customers’ buying habits, whether it’s social media data, mobile usage data, or specific data about customer wants and needs, you are building a profile of what your ideal consumer would look like. And once you have that information, you can target your marketing to a consumer group in a much more specific and effective way. But more importantly, big data gives you a real sense of what your customers want and don’t want, and how you can optimize your business practices to respond to their needs. Big data really comes down to customer expectations and how well companies are meeting or not meeting those expectations. Once marketers have the data, they can adjust their products, services and customer service to satisfy consumer wants and needs. And happy customers become customers who provide referrals, write great reviews and come back over and over to do business with companies that value what they find to be important.
Pam is the President and Chief Web Traffic Controller for Pam Ann Marketing.
“There are a multitude of free online tools that marketers can use to leverage big data to improve the customer experience…”
For example, at our digital marketing firm we make liberal use of Google Analytics to leverage insight into how customers are engaging with our clients. In addition to day-to-day traffic numbers, there are a lot of metrics in Google Analytics that marketers are ignoring.
Measuring bounce rate can provide insight into how customers feel when they first land on a web page. A high bounce rate means visitors are routinely landing on the page and quickly clicking on the back button. This is an indication that the web page in question is either not serving the customer’s needs, not creating a positive first impression, or a combination of both. Identifying pages with high bounce rates is a way to pin point areas where the customer experience can be improved.
Marketers can also look at metrics in Google Analytics such as time on site and pages per visit to gain insight into the type of customer experience the website is providing as a whole. If visitors on average are not spending much time on the website, or visiting many pages per visit, then that’s a clear indicator the customer experience can be improved.
Finally, we highly recommend setting up custom goals in Google Analytics to measure anything that’s most important for your business. Whether it’s newsletter sign-ups, contact form submissions, landing page visits, and so on. Obviously the more goal completions is a sign that the website is providing a good customer experience.
Having all of this data collected by a completely free too is one of the best ways we believe marketers can leverage big data to improve the online experience for their customers.
Lisa Myers is working as a Marketing Head at Game Period, a gaming website.
“There are different forms of Big Data…”
For instance, E-commerce platforms, Mobile Applications, and social accounts. The best way to leverage big data is to combine all these things into a synthesized data set, which will give a simplistic and holistic view of all the customer’s transactions. You can adopt a customer management platform for this.
William Cao is the Chief Analytics Officer for Catalyst.
“Marketers can leverage Big Data for customer experience insights using…”
Segmentation Analysis. Back in 1945, George Orwell wrote in Animal Farm that all animals are equal, but some animals are more equal than others. As marketers, we know that all customers are not created equal. We should be able to generate higher ROI by segmenting customers properly so we can target higher-value propositions to higher-value segments and improve our communications strategy.
So why don’t we? I’m convinced there are two reasons why:
- Many marketers believe they already know who their best customers are. This group is usually quite surprised to find out otherwise. Proper segmentation can be a humbling experience.
- Many marketers overcomplicate the process. The wide range of analytics tools and processes at our disposal, coupled with the expectation to come up with new and better solutions, often drives the temptation to create complexity. As a result, one of the biggest challenges-and opportunities-with segmentation is starting simple. Let me introduce you to a reliable, effective way to start simple: the 80/20 rule.The 80/20 Rule: How to Measure and Determine Customer Value by Segment
It’s an old axiom that 20% of your customers will produce 80% of your sales. Turns out, it’s true. The trick is figuring out which 20% is the right 20%. But once you’ve gone through the exercise, you can precisely focus your marketing strategy based on what each data segment is telling you. Each segment will yield a secret that tells you which customers are worth retaining, which ones you should try to win back, which customers are worth cultivating, where to prioritize your marketing spend, and who’s actually costing you money to keep. Do you really know who your best customers are? Here’s how to start.
1. First, determine your value segments based on whatever criteria drive your business: for example, sales, margin dollars or unit volume.
- Now, rank your customers from highest value to lowest value for the most recent 12-month period. The customers who produced 80% of total value are your High Value segment. The balance is Low Value.
- Now, do the same thing for the previous 12-month period and you will have High and Low Value segments from last year and this year. You’ll also have new customers who had zero value in the first year but are now on the books as High or Low Value customers. Likewise, you’ll have lost High and Low Value customers from the first year who had zero sales in the most recent year. A simple cross-tab of these dimensions is likely to show significant movement from one segment to another for each year.4. Now, rank your customers from highest value to lowest value for the most recent 12-month period. The customers who produced 80% of total value are your High Value segment. The balance is Low Value.5. Now, do the same thing for the previous 12-month period and you will have high- and low-value segments from last year and this year. You’ll also have new customers who had zero value in the first year but are now on the books as High or Low Value customers. Likewise, you’ll have lost High and Low Value customers from the first year who had zero sales in the most recent year. A simple cross-tab of these dimensions is likely to show significant movement from one segment to another for each year.Each of these segments presents opportunities to impact customer behavior and grow ROI if you understand what happened and why, if only broadly. For each segment, what you’re looking to learn is, what can I do to move you forward? Your goal is to drive customers into higher value segments. For example, what can you learn about the customers who moved from Low to High to better determine marketing spend for those who remained Low? Looking at the customers who moved from High to Low, how might you proactively avoid value loss next year among High Value customers? Once you understand what each segment tells you (the data), your job is to ask what happened? and why? (the analysis). Each intersection in the matrix begs important but often overlooked questions-the answers to which should shape marketing and sales strategies to prioritize marketing spend, drive growth, minimize attrition and churn, and improve ROI.What other secrets can you find hidden in your data? How about customers who should be marketed to less frequently, customers who shouldn’t be marketed to at all, lost customers to target for win-back, and clues to develop a more effective acquisition strategy. And the good news is, you don’t have to choose between these objectives. You can do them all, and you should. But the 80/20 segmentation matrix will clearly illuminate your red flags so you know where to focus first.
Becca is a Content Specialist at FM Outsource. When she isn’t planning and creating new content, she spends her time obsessively refreshing her Twitter feed and watching YouTube videos.
“Marketers can leverage Big Data for customer experience using…”
Google Analytics, which is the source of big data for any digital marketer. The wide range of reports it makes available means even if you’re only using GA, you’re likely to have access to the data you need for detailed insights into your customers’ experience through your website. Perhaps the best report is the behavior flow report, which enables us to see if/when people fall out of the sales funnel. We can also use it to see from which pages customers most often navigate to the support center of a client.
Max Page is the Founder of CouponHippo.in and has been in eCommerce and online marketing for 10+ years.
“To best leverage Big Data for customer experience insights…”
When running an online campaign, you should be using Social Listening & Sentiment tools to help you track the reach of your campaign. Listening tools will handle all the big data for you and help you track hashtags, keywords, @mentions and location check-ins. If the tool you choose also has sentiment analysis of all the chatter on the networks, it will be easy to see if your campaign is well received or if you need to tweak your messaging for next time.
Does your company leverage Big Data for CX insights? How do you leverage your data to enhance the customer experience?