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Of late social media platforms have become essential tools of marketing tools for all types of businesses, including retail. Nearly 70% of the active Facebook users in the US and Canada follow local businesses. A survey found that nearly 40% of consumers make a purchase after having viewed the commodity on social networking sites alone. For any retail chain that is a big number. Having said that, here are some social media marketing tips to aid your business. |
Customers today are aware about social media, and are willing to try stuff out and maybe even write a review based on their experiences with a brand. In an ideal world blog reviews should take care of it provided the product is good. Sadly, the world is anything but ideal.
The success of a product does not depend solely on its quality but rather on the advertising that goes behind it. The traditional ways of advertising are costly and often beyond the financial reach of new companies. This is where social media marketing comes in.
Here is a guide to get your marketing strategies take flight:
• Start your product launch campaign with research: Before you start developing your products, try to gauge what your target audience will actually notice and respond to.
• Plan a campaign that creates interest: Make sure that the campaign keeps the interest of fans high and urge them to actively participate in them.
• Video – your most effective marketing tool: It is estimated that by 2017, video will account for 69% of all consumer internet traffic, and video-on-demand traffic alone will have trebled.
• Involve influencers: Influencers are people with followers and fans who quickly respond to any endorsements and recommendations.
• Celebrate the revelation: Celebrate the campaign by rewarding fans who participated, with special gifts and rewards.
• Don’t kill the buzz: Case study videos are a great way to keep the buzz, around your campaign for a while. Read more at:
For more information visit:
http://www.germin8.com/blog/6-steps-to-social-media-marketing-success-product-launch-for-startups/
Recently, email marketers are using the coupons. It was found in a research that 71% of the population say coupons sent in emails very useful. Email coupons can work very well as a promotional tool and can be effective when they are personalized by product preferences. Jordie van Rijn (author) in his blog writes how we can improve the usage of coupons to improve business. Read more at: http://blog.getresponse.com/making-your-email-coupons-work-harder.html
While data has always played a part in ad campaigns-like whether a potential customer was more likely to see an ad on billboards, TV, or radio-big data has enabled a new era of advertising. With the advent of big data, brands can finally turn to actual numbers and metrics to make decisions-and use technology to help automate those decisions. Specifically, the programmatic advertising industry has deployed big data technologies so that companies and brands can be more precise about who exactly they're targeting. They can rely on exact data generated from GPS on mobile devices, social networks, actual purchasing behavior, and direct customer contacts, and analyze it to pinpoint their target audience. By analyzing this diverse data stream along with 1st-party advertiser data, we can play the right advertisement at the right time for the right person. It’s no longer a question of whether or not you want to utilize big data—it’s a question of how you utilize it.
For more information visit:
https://www.mapr.com/blog/how-big-data-advancing-programmatic-advertising#.Vb-xSPmqqko
Customers are delighted to get gifts for companies. But, some companies fail to do so in a consistent manner. Companies might begin with good intentions, but sometimes they lose their way. Jake Sorofman (a former CMO), writes in his blog how companies sometimes fail to keep consistency. For more information, visit: http://blogs.gartner.com/jake-sorofman/in-customer-experience-consistency-is-the-new-delight/
Sepsis is a serious medical condition that occurs when the body releases the full force of the immune system in response to an infection. The immune chemicals trigger widespread inflammation that can result in impaired blood flow and thus leading to failure of the body's organs. This disease is consuming major cost for the healthcare industry. Here Data Analytics has stepped in and provided a solution. The solution consists of a disposable wireless Band-Aid-like biosensor (the FDA-certified HealthPatch), which helps in real-time processing of patient data, and consumable analysis that allows medical professionals to take immediate action.
The smartphone app transmits the patient clinical data to a cloud-based repository, where it is integrated with existing patient data from other data sources (NoSQL and SQL-based data sources, premium data sources, etc.). For more information visit:
http://www.cio.com/article/2949854/big-data/how-big-data-analytics-help-hospitals-stop-a-killer.html
In order to increase standards of the capital markets post-crash and other unprecedented events, few regulations enforced by the market regulators are forcing the market participants to have a more thorough background research. Thus demand for data in capital markets is increasing as never before. The analysis reports are now being made at real time to increase the efficiency, and quality. But the problem at hand is how well firms can handle this data. Can they afford the data within their profits? Can data can be made available to all in proper usable format to all the participants at minimum price. How can the data made available be kept clean and free from corrupting? To read through some of these issues go through-http://www.automatedtrader.net/articles/feature/153959/the-data-deluge
The term Internet of Things was coined in 1999 by Kevin Ashton, cofounder of the Auto-ID Center, an RFID research project at the Massachusetts Institute of Technology. IoT is about intelligent devices talking to enterprise apps. Its important to focus on the basic building blocks as the success of an IOT initiative depends on them. However, you must overcome challenges before the IoT can be fully realized. A lack of unified standards , Complexity are some of the challenges. If you're starting from scratch, it's important to ask, "What's the No. 1 business problem you want to solve?" Once that's answered, it's time to look at the systems you need to connect and the capabilities you must put in place. The most important point is to bring your structures and unstructured data together in a meaningful way.
Read more here- http://www.cmswire.com/internet-of-things/get-ready-for-the-iot/
Does your analysis show more revenue than what is actually being generated? Or you are getting results that are too skewed to make actual sense? Make sure you follow these 3 ways to avoid making data driven mistakes
1) Get right data: make use of latest data and look for duplicate, missing values and outliers. It is also imperative that you have enough data while drawing an analysis.
2) Ask questions: Sometimes analysts apply techniques they haven’t really examined. Asking questions makes you better understand the problem at hand
3) Make productive use of spread sheets: if while looking at data, you are looking at spreadsheet, remember to keep data and formulae separated.
Read more at: http://www.forbes.com/sites/teradata/2015/07/08/how-to-make-a-bad-data-driven-decision-in-three-easy-steps/
Many experts believe the model for Internet of Things (IoT) will be smart sensors communicating directly into machine clouds. Edge computing is a critical element needed for the advancement of the IoT. Here is 7 reasons why: 1. The edge is the muffler for data exhaust
2. Time can matter as edge processing reduces time spent.
3. Configurability is an important clause in shaping the future of IoT.
4. Implementing a secure IoT.
5. Governance will become more important.
6. The proper architecture will be needed to accommodate the market demands.
7. Cost as edge processing will be costlier in most cases.
To know more: http://www.thoughtsoncloud.com/2015/07/7-reasons-edge-computing-is-critical-to-iot/
There is a fear attached to the security of cloud. However these are myths. Some are:
1. Cloud is riskier than traditional IT: Data breaches can happen on premise. The efficient way is to work with a competent, experienced provider that invests in strong network securities.
2. You can’t control where your data resides in the cloud: regulated industries like health care require valuable information. This is discredited because organizations can choose specific region based data centers, private clouds.
3. The cloud is not suitable for complaint workload: organizations can leverage for private or hybrid cloud development model better suited to the needs.
To know more, follow: http://www.information-age.com/technology/cloud-and-virtualisation/123459832/3-myths-about-cloud-and-security
Data blending means combining data from multiple database sources into a single worksheet or table of a given solution in a relatively quick and straightforward way for discovering pattern between data. Big Data blending is gaining importance in businesses as data blending allows uncommon types of data to coexist in a model. New and better strategic decisions can be made by bringing together unusual feeds into one repository. Data blending and data joining are not similar and have significant differences. Joining involves combining data from the same source whereas blending involves combining data from different sources.
Read more at: http://www.cmswire.com/analytics/how-data-blending-can-sweeten-your-insights/
Increase of a site's traffic is normally taken as a brand's visibility and relevance. But often things are not what they appear to be. Hence for making out whether the visitors are real or not data, leveraging is required. Establish What “Normal” Means for Your Business – The data and tracking should be made by such a source that in case of a drastic change the problem can be isolated and identified. In order to recognize what’s normal and what’s abnormal a baseline to work from has to be established. The performance data has to be reviewed consistently and methodically.
Not All Spikes Are Bad Spikes – Identifying whether abnormal spikes in the site traffic or analytics is good or bad is difficult. Logistics issues can be alerted by sudden spikes and dips.
Common Sense and Logic – Looking for twists and reviewing behavioural flows to identify pattern of users can be employed. This helps in understanding the key attributes of the traffic or the keywords. The emerging patterns can be used for proper optimization of the flow of the site.
Read more at: http://www.cmswire.com/analytics/ask-your-data-is-it-a-bot-or-real-traffic/
Big data for a long time has been handled wrongly, as there is problem lies in assigning meaning to data. There is acute skill shortage and the human factor also complicates big data. Here are a few ways how we can get better benefits from big data.
1. The business has to say what it wants to achieve from collating and analyzing data.
2. Asking relevant questions, so the data can provide answers.
3. Start small and then get bigger, trim irrelevant data.
4. Managing costs better
5. Understanding what data matters to the business the most.
To know more, follow: http://www.information-age.com/technology/information-management/123459617/big-data-phenomenon-broken-5-tips-doing-analytics-right-way
To provide correct business decisions, we need to address data quality consideration like accuracy, timely, consistency, etc. There is a sheer growth of data which needs to be accounted for and properly identified from the source. Quality movement focuses on many diverse aspects. The origins of defects therefore failed to be identified. The challenge is to understand the data, by use of data models and in context. Analysts build models based on continual consultation with business stakeholders. Metrics are established to quantify the relative importance and evaluate progress. Continual improvement is an ongoing discipline which gives breakthrough results and competitive advantage. To know more:
http://www.thoughtsoncloud.com/2015/07/enabling-a-data-culture-through-continuous-improvement/
People analytics is a data-driven approach to managing people at work. Those working in people analytics strive to bring data and sophisticated analysis to bear on people-related issues, such as recruiting, performance evaluation, leadership, hiring and promotion, job and team design, and compensation.
The 5-step path to people analytics:
1.Bridge the gap-To ensure you have everything you need- people, processes and technology
2. Knowing the stakeholders- involves understanding their challenges, goads and opportunities
3. Setting goals and objectives- This involves agreeing upon mutual goals and objectives
4. Assessment- Doing a reality check pf where you are and where you want to be
5.Prove success with data- Highlighting successes and areas that require improvement.
To know more- https://icrunchdatanews.com/5-step-path-people-analytics/
The increasing number of startups have surpassed the big players with data driven business models. Data science has become obsolete! The next big thing is predictive analytics.
But there are fears associated with adopting this new technology like the fear of complexity, replacement and failure.
How effective predictive analytics will be depends on how the organization perceives it. When everyone in the business starts thinking about how predictive analytics can improve their organization, it results in big wins for the company.
To move forward with predictive, the business needs to leave data science behind. Predictive analytics is a completely different approach. Applied to business, predictive models are used to analyze current data and historical facts in order to better understand customers, products and partners and to identify potential risks and opportunities for a company. It uses a number of techniques, including data mining, statistical modeling and machine learning to help analysts make future business forecasts.
To know more- https://icrunchdatanews.com/3-keys-smooth-migration-data-science-predictive-analytics/
Project management now a days requires a more flexible approach than traditional methods. This involves taking step by step actions which are ranked based on priorities.
4 Good Reasons To Do Agile Project Development-
1. Quality -A key principle of agile development is that testing is integrated throughout the lifecycle, enabling regular inspection of the working product as it develops. This allows the product owner to make adjustments if necessary and gives the product team early sight of any quality issues.
2. Flexibility- In agile development, change is accepted. In fact, it’s expected. Instead the timescale is fixed and requirements emerge and evolve as the product is developed.
3. Revenue -The iterative nature of agile development means features are delivered incrementally, enabling some benefits to be realized early as the product continues to develop.
4.Predictability – using an Agile approach with fixed schedule iterations makes the cost of each iteration predictable.
To know more-http://revenueanalytics.com/blog/agile-project-management-benefits-to-a-revenue-management-project/
A U.S. regional bank while reducing its staff and technology cost wanted to see how it could maintain its collection rate. A consultancy based in Chicago and Bangalore analyzed the actions of a U.S. regional bank such as calls, mailers and IVRs and concluded that the bank was overspending. The bank was thus able to reduce costs by a million $. Analytical companies are now investing in platforms and products to fill the void in analytic stack. To know more:
