Technology Enthusiasts: 3 Action Items to Bring a Spark to Your Company

Siri, Cortana, IBM Watson, Viv…Humans are building smarter machines to better serve the needs of…human beings. Artificial intelligence has become so hot a topic that every technology enthusiast should be curious about. As a grad student at the Northwestern Medill IMC program, I have found two articles that you, as a technology enthusiast, might find interesting.

An article by Will Knight from MIT Technology Review talks about deep learning and misunderstandings some people have on artificial intelligence. In an interview with the publication, Bengio, a professor of computer science at the University of Montreal, states that although deep learning helps make some progress in developing artificial intelligence, machines are still far from being intelligent or threatening human beings. Unsupervised learning and natural language understanding are two major unsolved problems with developing a revolutionary AI. AI is cool and could change the world, but people shouldn’t be over-excited or overwhelmed because it’s still at its baby stage.

A second article by Heather Kelly from CNN Money talks about Mark Zuckerberg’s perspective on artificial intelligence. Mr. Zuckerberg agrees that unsupervised learning is the key to advance artificial intelligence and plans to build his personal AI assistant this year. He believes that self-learning AI still has long way to go and people shouldn’t be afraid of it. Instead, it’s possible to make good use of it.

As a grad student at Northwestern, with a strong interest in technology and data analytics, I recommend the following three action items to anyone who shares similar passion:

• Think AI - Artificial intelligence is worth noticing, learning, and investing or contributing in other ways.

• Grow Together - Researchers and engineers have made some progress but still far from making real intelligent machines.

• Be Fearless - Artificial intelligence is not evil or dangerous, at least not at this moment.

Whether you are a student, an employee, an employer or an entrepreneur, as long as you are a technology enthusiast, these three tips will make you stand out from your peers and give you a head start when you develop a career in TECHNOLOGY.

Yuchen Luo @blazermania1

Personal website

Yuchen Luo is a full-time student in the Medill Integrated Marketing Communications program. After completing his undergrad at USC majoring in Business Administration and minoring in Sports Media, Yuchen worked for a Santa Monica ad agency where he analyzed consumer, competitive and campaign performance data to provide insightful media planning recommendations. This experience opens up his interest in the application of data analytics in marketing and advertising. Beyond data analytics, he is developing his new found interest in coding by taking online coding courses and training programs. He is super passionate about technology and his long-term career goal is to help a technology startup succeed with his all-around skill sets in data analytics, marketing, and strategy consulting.

CMOs: 3 Ways to Accelerate Big Data Analysis Transformation in Your Company

Big data is exciting. As a CMO, you know Big Data is becoming more and more critical to your business' success. As an IMC graduate student in Medill School of Journalism, Media, Integrated Marketing Communications in Northwestern University, I’ve been doing some research in how traditional companies transform into a data-centric company, and here are two articles that best address the issue.

The first article, titled “Getting big impact from big data” by David Court and published in January 2015 talks about how to take advantage of advancements in analytics and mobilize the organization to make a big impact on the company from big data. New data analysis techniques and tools are introduced to deal with the challenge of achieving scale of impact. The real challenges lie beyond new tools, and ask for more focus on change management, more job redefinition, and more cultural change.

Another article talks about data transformation is by Derek Steer, the Co-Founder/CEO of MODE.  This article, titled “Building credibility for your analytics team- and why it matters”, published on January 21^st, 2015 focuses on how to build credibility for the analytics team in the company and over time turns the company into a data-centric firm. First start with simple tasks, then analyze and communicate effectively with colleagues, think data as a conversation starter, not a diagnosis, and make the process of data analysis transparent and understandable to other teams.

After reviewing these articles, and based on my experience through the IMC program, here are three action items any CMO or marketing manager should immediately begin to think about and take actions on:

• Start small - Start with simple tasks that give immediate returns. This establishes the trust and over time builds confidence in the company.

• Redefine jobs - Automating part of the jobs requires redefining job responsibilities to best leverage and support the ongoing development of big data.

• Change culture - Build a foundation of data-driven culture in the company by developing competitions that reward and recognize the teams that can generate powerful insights through analytics.

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I am currently a graduate student in Northwestern University Medill School, and major in Integrated Marketing and Communications. I will graduate in December 2015 and am looking for employments in data analytics. If there is anything you would like to discuss with me, you can reach me @AmeliaChenZhao on Twitter.

CMOs: 3 ways to avoid big data mistakes

As a CMO, you know Big Data is increasing market share and bottom-line profitability for all types of businesses...only if you do it right. As a graduate student in the Northwestern Medill Integrated Marketing Communication program with an interest in data analytics, I have found 2 article highlighting important concepts about using Big Data successfully. 

Information week’s article Big Data Success Remains Elusive: Study reveals a cruel survey result that only 27% of the organizations described their big data projects as "successful". This survey is conducted by Capgemini Consulting involving 226 company respondents across regions and multiple industries. According to this article, big data failures are primarily the result of: 1)Inconsistency between big data analytics and business objectives. 2)Attempts to use their existing data management systems to process big data stream. 3)Scattered silos of data resulting in a lack of unified view of data. This article also suggests key success factors for big data approach, that is “a well-defined organizational structure”, “a systematic implementation plan”.

sources:  http://www.coredigitalworks.com/

Shanker Ramamurthy, Global Managing Partner of IBM, holds a similar opinion in his article Speed To Insight: Key To Big Data Success: Big data analytics should become ubiquitous across different departments in the business organization, including HR, sales, marketing, and etc. Another important factor he put forward is “speed” from data to decision-making. The case of Wellpoint http://www.antheminc.com/ is used to illustrate the importance of speed. This health benefit company implemented a system that quickly correlates clinical research, patient data, and clinical practice guidelines to shorten the pre-approval process so nurses are given best options for each patient in a matter of seconds. By doing this, WellPoint is reducing costs improving service, as well as catering appropriate treatment for each patient.

Based on these two articles and my industry studies as a graduate student in the Northwestern Medill IMC program, here are three actions I would recommend

to companies that want to succeed in big data approach.

l     Share Big Data Organizationally: Big Data Analytics impacts across divisions and requires integration of multi-sources. So create analytics teams to gather and use data uniformly throughout your organization

l        Bring into decision-making: Don’t isolate Big Data Analytics from you business process. Make it the engine to drive your business decisions and actions

l     Accelerate the speed: Shorten the time from data to insights . Be receptive to changes as business market is becoming real-time basis. Take timely actions accordingly!

In today’s business environment, becoming Big Data-centric is a shortcut to become competitive. While, as every other front-edged technology, big-data is like a vitamin tablet that take time to digest. In current stage, business organizations are still attempting this technology while separate it from its business process. I believe real benefits will be realized when big data analytics will be into its decision-making process as well as into operation across different departments in a timely manner.

Jill is a current master student in Northwestern University, studying marketing analytics. Before that, she graduated from Tsinghua University, experienced in management consulting and strategic marketing planning. She is dedicated in delivering actionable strategies and in-depth insights through data-driven methods. Feel free to comment and repost. Jill can be connected through Twitter and Linkedin. 

CMOs: 3 steps to integrate big data analytics into CRM

As a CMO, how you integrate big data analytics into your customer relationship management systems could spell the difference between success and failure in today's data-driven marketing era. As a graduate student in the Northwestern Medill Integrated Marketing Communications program, I have found two articles that can help you learn more about CRM analytics and its impact on building a comprehensive understanding of your customers’ needs and preferences. 

The article “The Future of CRM Analytics is AlreadyHere” points out the importance of applying analytics to customer relationship management efforts.In order to gain a 360-degree view of the customer, many companies have blended customer data, operational and transactional data and data analytics to develop comprehensive understanding of their customers. The integration of data analytics and CRM has proved success- the complete views of customers resulting from the integration have enabled these companies to generate meaningful insights about marketing campaigns and put them at a better positioned to identify and act on cross-sell and upsell opportunities.

source: http://crmsolutions.crmnext.com/

In the article “Five Reasons Why CRM Analytics are Essential for Success”, Marianne Cotter explains five reasons companies should integrate data analytics into CRM and use data and CRM analytics to tailor the customer experience for improved engagement and better profits. The five reasons she points out include better customer understanding, better understanding of the customer-facing operations, decision support, predictive modeling and benchmarking.
Based on these two articles and my graduate learning in the Northwestern Medill IMC program, here are three action items I recommend you consider:

• Adopt real-time and predictive analytics - be aware of real time tools and utilize them to process data in real time to connect with customers more immediately and deliver highly personalized experience. Tie predictive analytics with CRM to learn more about customers' buying behavior.

• Create expert team -recruit people with complementary skills who can bridge big data analytics with CRM. Have people with analytical skills who can understand structured and unstructured data working with business managers and IT people in a team.

• Cultivate interaction - besides monitoring customers and conducting big-data analytics on social media, interact with your customers by providing them more customized opportunities.

As a CMO in today’s data-driven economy, you really need to start thinking about harnessing the power of big data and integrating data analytics into CRM to facilitate smarter sales and better customer engagement. I recommend you look at these three action items and use them when develop a future strategy for big data and CRM.

Xinwei Zhang is a M.S. candidate of integrated marketing communication at Medill School, Northwestern University, specializing in Marketing Analytics. She is going to graduate in December 2015. With dual bachelor degrees in Psychology and Consumer Economics, she is passionate about analyzing consumer behavior and synthesizing data to actionable insights, stories and marketing solutions.
Any questions and comments? Contact me on Twitter or LinkedIn.

Fashion CMO: See what happens when Fashion meets Big Data

    As a fashion CMO, you may have noticed the huge impact Big Data has made to the business world. We can’t help wondering, what will Big Data change the Fashion world that we deeply love so much? What will happen when Fashion meets Big Data? As an Integrated Marketing Communications student at Medill School of Northwestern University, and a keen fashion follower, I have identified two articles that define the importance of big data in fashion industry.

    The first article “Big data may be fashion industry’s next must-have accessory” states that big data may become the next new thing to hit the fashion industry’s runways. Researchers were able to identify a network of influence among major designers and track how those style trends moved through the industry by analyzing relevant words and phrases from fashion reviews. While professionals in many industries are welcoming data analytics, this type of analysis may meet some skepticism from fashion designers, who view their work as a form of art and more difficult to quantify. Fashion styles may also be predicted by analyzing real-time data from social media sites, such as Twitter, Pinterest and Instagram, which is pretty cool.

                                
                                                          Source: Cable Fashion Show

    Similarly, this article below "What does data and analytics mean for the fashion industry" states that by using tools such as Google Analytics, the fashion industry should be able to accurately forecast what consumers want to buy and not what designers want them to buy, hence they will be able to end up growth-hacking their business. Social shopping sites, such as Krush, have worked wonders in connecting the predictive power of analytics and e-commerce in the fashion industry. If we can get the right information about the right fashion to the right people at the right time, businesses will be able to make the right business decisions to forecast the next fashion trends, which is the rise of “Fashion Analytics”.

    From my studies from these two articles and my data analytics background in the Medill IMC program, I think there are several steps can be followed to think about improving “Fashion Analytics”, since it’s becoming the heart of almost all the fashion industry developments:

• Develop Better Analytics - Better data analytics can directly help improve profitability. Better data analytics can help optimize every aspect of the fashion business, including the supply chain, customer segmentation, spotting hot items, monitoring profitability. 
• Create Social Communities - Social fashion communities have become extremely important, you shouldn’t ignore. It has become a real-time source of data analytics for consumers and brands alike, and social network analytics can reveal who are the key fashion influencers.
• Utilize Analytical Customization - Customization and iteration become doable. It is now possible to create more “data analytics” fashion. Companies can move to a more iterative, analytics-based customized approach, where clothes are made in smaller batches based on the particular desires of an individual or community.

    In all, big data is starting to influence fashion industry in every way, and more is yet to come. Through social media, which is bigger than you think, the industry is opening its door to millions of fashion chasers who are eager to share their opinions. The brands can then extract the most wisdom from the tremendous data resources and change them into actionable strategies.


The author, Yun Xu "Betty" is an integrated marketing communication graduate student at Northwestern University. She is particularly interested in turning data into actionable insight and marketing strategy in the fashion industry, therefore to improving ROI. You may contact the author via twitter: @xuyunbetty and LinkedIn: @Betty Yun Xu

Use Big Data to Make Big Impressions with Consumers in 3 Easy Steps

As a consultant, it is important to evaluate the state of your customer's database. The amount and breadth of information available can drastically change the strategy behind customer service, marketing and even product development. As a graduate student studying Integrated Marketing Communications at the Medill School at Northwestern University, I have found two articles that address the ways that business can use customer data improve service, engage their customers and start taking steps into the big data world.

In 5 ways companies are using big data to help their customers, VentureBeat gives a great overview on how companies should be using big data to help predict customer needs and how utilize feedback to improve pain points. They also note how you can improve customer service interactions by having more robust information such as how the customer has engaged with the company socially or any past purchases. For businesses with a customer services focus, making sure the service metrics are being plugged into your database can help you identify trends as they happen, so you can know what to focus your energies on the most important opportunities in real time.

Image courtesy of David Castillo Dominici / FreeDigitalPhotos.net

Still at a loss on how you can make big data work for you? Nicole Fallon of Business News Daily instructs businesses to leverage their internal information to build out customer loyalty programs in her article Boosting Customer Loyalty with Big Data. The loyalty programs, or even a baseline customer newsletter can help engage customers to buy more of your products and boost sentiments towards your brand. This is excellent advice as most business are probably not utilizing their customer data to its fullest and even simple analysis can help you identify customer that could spend more if they were part of a loyalty program.

After analyzing these two articles, here are three action items you need to implement to start tapping the power of big data:

1. Get your data in order

The usefulness of big data can be hindered by what information you have available on your customers. From contact information to purchase history, be sure that you have an accurate and reliable database solution and try to maintain as much information about the customer journey as possible.

2. Listen to your customers

Now that you have some quantitative data on purchase history, work to include qualitative points based on customer feedback to help move your business forward. You can gain insights from surveys, social media monitoring and even service representatives if available. These insights can help make your products and service better for returning and new customers alike.

3. Communicate with your customers

For the majority of small business, more than half of their annual revenue comes from repeat buyers, which makes cross selling your other products key. In addition to introducing new products and services, useful news and best practices for your specific industry can help create value for your brand. Be sure to set goals attached to your outreach, whether they be to increase sales or even just to improve engagement.

Big data can seem daunting depending upon where you are in the process, but by taking small steps you can get headed in path to better utilizing information you already have. If you haven’t gotten started yet though, consider this your wake up call. If you won’t take action and use data to improve your customers interactions with you company, your competitors certainly will.

Jay Hover is the Senior Manager of Customer Engagement at Rakuten Marketing, an ecommerce marketing services firm specializing in affiliate, display, search and retargeting. He oversees internal client communications and is responsible for engaging more than 2,000,000 partners. Jay is currently pursuing his M.S. in Integrated Marketing Communications from the Medill School at Northwestern University and is a graduate of the University of Wisconsin-Madison.

Follow him on Twitter @jmhover or connect via LinkedIn: www.linkedin.com/in/jaymhover/.

Strategists and Data Analysts: Make the Deliberate Connection and Really Excel as Data-Driven Strategist

As data analysts and strategists, being data driven and strategic is really two sides of the same coin, the key is to make the deliberate connection. Being told you are not strategic or data-driven really stings, but despite thousand hours we spent on drawing up detailed plans and investigating data, all too often thy matter every little to performance. As an IMC graduate student in Northwestern's Medill School, I have been focusing on bridging strategic planning with data-driven analytics and I found two insightful articles from Harvard Business Review and McKinsey Quarterly that will help to tear down the Great Chinese Wall between the art and science of marketing communication. 

Being strategic is fundamentally making deliberate connections. In Strengthen Your Strategic Thinking Muscles, Liane Davey argues that sometimes we are just too busy to be strategic. Under the guise of productivity, we have probably squeezed out thinking time, thus the decision is based more on reflex than reflection, more on what has worked before instead of making meaningful connection. Every one has opportunity to be strategic, simply by being more deliberate in our thoughts and actions. Down to the execution level, being strategic also requires making choices and connect things and domains that is currently separated or segmented.

Big Data is now the buzzword everybody is uttering, but few people realized simply collecting Big Data does not unlock its potential value. In Big Data help wanted (badly): How to win the war for talent, McKinsey on Marketing & Sales argues to true tap into the analytical power of Big Data and form data-driven strategies, strategists and analysts should aim at being “translators” who are capable of connecting different business functions and effectively communicating between them. These strategic connection making process is really the prerequisite of being strategic under the Big Data context.

Image Source: McKinsey on Marketing & Sales

Based upon these two articles, I realized there are three action items that could really help to be strategically data-driven: Strategy and Big Data are the most misused and overused words in our business, but instead of being isolated, they are actually complimentary. As the author of Predictive Analytics Eric Siegel once criticized, "big data often means small math", big data can also means meaningless strategy. Being strategically data-driven is really the benchmark for strategic and analytical talents, and that requires strategists really reflect on the true meaning of being strategic and make the deliberate connection between different business functions. 

1. Make more time to reflect before making decisions. 

2. Be courage to make choices and embrace the uncertainty.

3. Create connections between analytics, technology and business decision making.

To be strategic and data-driven are among the biggest expectation of today marketers, all too often they are referred as the “art and science” and seen as hard to reconcile. However, I believe they are actually complimentary and symbiotic. Being strategic is fundamentally about making deliberate connections, and it is even more so in the Big Data context. Marketers to seek to be more strategic need to actively bridge and communicate with different business functions. They can thus become “navigators” and “translators” and truly empowering strategic decisions. 

Aaron R. An is M.S. candidate of integrated marketing communication at Medill School, Northwestern University, specializing in Marketing Analytics and Brand Strategy tracks. Aaron graduated from Peking University with bachelor degrees of Economics and International Relations. Prior to IMC, Aaron worked in Caterpillar’s China strategic development department, Ogilvy PR’s China Outbound Strategy Practice, and Northhead Consulting, helping Chinese companies to form their outbound marketing strategies and US companies to form the localization strategies. 

Any questions or comments? Contact him on Twitter at @Aaronarpku

Analytics Managers - Today, Real-time Marketing Analytics Rules

Marketing Analytics Managers are now able to track market trends and insights of the last minute by utilizing real-time analytics techniques. As a graduate student at Northwestern University, Medill IMC with the specialization of Marketing Analytics, I have been following the news and papers of the practice of real-time marketing and I am happy to share two articles I like.

Big companies are the first ones to put the real-time analytics into practice. Paid more than $200 million for Topsy, Apple's acquisition of this real-time social media analytics start-up is considered as a long-term strategic investment. In Adam Satariano's article "Apple Buys Real-Time Access to Twitter's Feed With Topsy Deal", Debra Aho Williamson, an analyst with EMarketer Inc., believed that Apple will use the real-time social media analytics for analytics of the iAd mobile-advertising service, to make purchase recommendations from iTunes and App Store, or other marketing acts. Instead of getting market reports from the analytics group once a week, real-time analytics will easily provide more accurate insights for analytics managers to tailor messages to target audience.

Real-time marketing analytics is not only desirable for technology companies like Apple, Coca-Cola and Pepsi are both touching the area of real-time analytics. The article "Big Marketers Have Real-Time Data for Just About Everything" by Christopher Heine shows us how the real-time analytics company, Bottlenose engaged with big names like Coca-Cola and Pepsi. Bottlenose monitors and analyzes data includes all brand mentions that is collected from most of TV and radio around the world. They can even visualize the market-leading sentiment analysis at real time. "Bottlenose does real-time trend intelligence for brands across social, television and radio in one system. We figure out what's trending across all media in real time and show you what drives what." says Nova Spivack, CEO of Bottlenose.

Based on my study and review of these two articles, here are 3 things marketing analytics mangers should do to have the best performance of real-time analytics.

1. Analyze Best-of-Breed Examples. Learning from real cases is always a good way to learn and improve, especially for new techniques. Analyze the big companies' real-time marketing acts will help us understanding better about how to drive the most benefit for our company from real-time analytics.

2. Identify real-time analytics demands. Even if your company is not using real-time analytics now, you should pay attention to the times when real-time analytics could help you improve your marketing performance. Knowing that will make you have a better use of real-time analytics.

3. Explore new real-time marketing strategies. Not only to improve the performance of existing marketing acts, it is also useful to take a look at the real-time data and come up with brand new real-time strategies.

Data are everywhere the whole time. When we gradually started to benefit from big data, real-time data is now the time to be the new weapon for Marketing Analytics Managers.

Jason Zhixun Wang (@jasonzhixunwang) is a marketing analyst who is passionate in utilizing data mining techniques to interpret mess big data into actionable marketing insights. He learned and practiced restructuring, aggregating big data with analytical tools such as SAS, R and SPSS and interpreting the data. He has done marketing analytics projects for companies with professors at Medill IMC Spiegel Digital & Database Research Center.

Feeling empowered by Big Data

In today’s economy, business leaders and marketing executives must understand customers’ needs and behaviors to strengthen their competitive advantage. These valuable insights can be discovered by sifting through Big Data and identifying patterns. I’ve focused on analytics and behavioral marketing as a graduate student at Northwestern’s Medill IMC program to strengthen the skills that lead to such valuable discoveries. 

"Big Data: Cutting through the Noise"

In a recent article on the Discovery Channel’s News website, Big Data collected through self-tracking methods was predicted to become more prevalent with every advancement in data processing speeds. Experts in economics, psychology and health care expect “that personal monitoring devices will become so cheap and unobtrusive [in a few years]...that they'll be ubiquitous.”

Nick Barthram of Indicia offers several suggestions on how to more accurately identify true insights from Big Data rather than allowing “confirmation bias” (among other evolutionary traits in humans) to lead us to spurious correlations in an article he wrote for WARC’s AdMap: September 2013.

So don’t get overwhelmed with the thought of having to find (and of course validate through testing) an insight from massive data sets. Just follow three actionable steps:

    1) Embrace: As time passes, only more data is collected so avoiding it or ignoring

              what the data might be telling you is not an option if you want your

        company to be successful

    2) Challenge: Don’t blindly trust what the correlations an algorithm have formed from

         the data; as Barthram says, “Use testing to repeat the situation and

         check that it still stacks.”

    3) Stay Patient: It’s easy to rush to a conclusion and implement the information into a

business plan but time is for once on your side. The longer data spans,

the more likely it will show certain correlations as opposed to influences from external forces.

It’s time to take control of Big Data and make it work in your favor. That doesn’t mean drawing faulty conclusions to support a hypothesis, though. Stick to your clearly defined business objectives that support your strategy. Big Data is only going to grow so feel empowered by the opportunity to discover valuable information from it. The old adage of “knowledge is power” has never been more true than it is today.

Today, marketing success requires data integration and experience customization

        To all data-driven marketing professionals in retail industries, we are all facing a data explosion era; you may collect a lot of data, but do you really utilize it well? Extracting insights from big data and enhancing the customer's experience will be a key challenge for all of us. As a master’s candidate of the Integrated Marketing Communications program at Northwestern University, I want to share two articles with you. 

   

        Firstly, mobile apps have changed consumer behaviors toward searching and shopping. While improving functions of apps to attract customers, retailers should also grab the chance to utilize more data from mobile devices and integrate that with data from other mediums. Smart retailers don’t just collect data; they see the big picture, transforming the data into brand stories and experience customization. A vast amount of data from mobile devices is the new gold mine. It not only enables us to improve customer service, but also helps us to improve other business problems, such as employee relations. I found an article in The Jordan Times. It showed several statistic trends of mobile device that you might find interesting: Mobile devices, dataanalytics key to businesses future growth —experts

   

        However, knowing what kind of data we can extract from multi-media is still not enough. How can retailers use that to improve customer engagement? Today, the power of word of mouth influences customer retention and acquisition, and the key factor that drives word of mouth is customers’ experiences toward the brand. In this intensive competition, only brands that utilize insights from data to customize customers’ experiences will be crowned. Here is another article on Forbes that may help you to think about that: Customer ExperienceControls Business Growth Today

  

        To summarize these two articles, we should start to do the following things:

           

•    Link data from different mediums in order to see the big picture. 

According to the second article, consumers have turned “omnichannel”. Therefore, in order to maximize the usage of different channels’ data, such as from mobile, linking data from different platforms is essential for brands. Retailers can establish a multi-dimensional customer profile about where and when customers search, shop, and give feedbacks. While merging data and linking key identifiers together, marketers can see the big picture and avoid falling into silos.

•     Utilize data to improve experience customization    

Data is dead, only storyteller can make it alive. Stop collecting data and then putting it away! Retailers should re-evaluate current datasets and extract consumer insight. By segmenting different customer groups and digging into customers’ preference and behaviors across different media platforms, we can better understand what they really want and take the chance to outshine competitors. These insights will tell customers’ stories and really help the brands to engage and customize customers’ experiences.

•     Differentiate your apps from others and deepen the customer engagement.           

Since mobile has been an important tool for marketers to collect data, how to keep engaging with customers and consistently communicate with them define the winner in the long run. By analyzing data, retailers can find niche advantages to establish their apps’ uniqueness, and also get more useful data from consumers. Two birds, one stone.

        By executing the actions above, marketers are able to extract insights from data in multiple dimensions and increase a brand’s strengths. In addition, since the mobile market hasn’t reached the mature period yet, every brand has a chance to win. Why not starts it now?

   

Contact information of the author:    

As a master’s candidate with proven data analytics and consumer insight professions, Flora Yang will graduate in December 2013. She is looking for marketing analyst positions in retail, CPG, financial and agency industries. Reach her on Twitter: @finverota or via LinkedIn.