Shelf Life of Trends

Shelf Life of Trends- A concern for big data analytics era

Shelf Life of Trends- A concern for big data analytics era

One the  most grappling challenges for  business in this era  of  big data  is how  long does  each trend remain a  ‘trend’. With the high rate of idea  metabolism , with the increasing rate  of  technology and innovation driven  change , trends get more and more  short lived.

A trend is essentially based on a period of data and more the period the more  reliable it gets. And this period has minimum factors changing be it government policies, economic factors, environmental conditions or technological advancements. But as  and  how these  factors change , this period of consideration gets  sliced and minced .  It gets  difficult to call it a trend. It is no longer  a  function of a long period of constant conditions. In fact, its the rate of  change of change that is more likely to become a trend.

For example –

Trend in the  demand for touch  technology is valid  only as  long as voice recognition is  not developed and  that in turn will not remain no longer relevant than the  invention and mass access to eyeball detection technology .

Question remains, if long-term climatic trend is actionable in project planning today, at what point do you revisit the trends analysis to verify that the projects you have forecasted for your pipeline are still worthy?”

An important step for most companies using long-term trends information garnered from analytics will be to determine how long they can expect the analytics for each trend to remain accurate and usable for business decision making . Organizations have not yet moved forward into long-term trends usage and decision-making, but as more do, they will also need to apply their own analytics to the longevity expectations for the trends data they capture. “It is determinations like this that sit on the doorstep of the next frontier of big data analytics”

About Hedgehog Insights– We are data analytics service provider . We offer analysis of business data. Be it daily operations, cash flows, website data or ones from social media, we analyze all of them together, on one platform, draw, connections, correlations, causes and offer our clients set of easily actionable insights. Tools are really in abundance and we are not selling another expensive one, all that we are sellingis a promise that our analysts will offermodern and conventional analytics , work with you and help you see hidden opportunities from your business data.Schedule a free consultation

Data Don’t Do- That’s left for You!

Business Analytics and importance of a plan to execute!

The importance of data today can never be overstated. More now than ever before with disruptive concepts like big data and all the great information it can yield, businesses are making a serious effort to adopt analytics services.  And so is the surge of tools and applications with promises to make their job simple.

All businesses, ones producing the food we eat to those drafting insurance policies heavily depend on insights from analytics. Some run short term subcontracted project while others build an in-house teams of top class statisticians and BI experts to ensure a constant flow of insights.

And why not- these are scientifically derived tips into what to do and what not to do in business has borne sweet fruits too…

 

For McKessen , the model development necessitated the creation of a data analytics support structure of related business intelligence that did not exist before. The sheer magnitude of the number of transactions processed each day made the project challenging. McKesson Pharmaceutical Supply handles 60,000 active items in 30 distribution centers shipping two million pieces a day to 25,000 customer locations. The new data analytics has been the source for a multitude of business projects that would not have been possible before this model and is the basis for quantifying the financial impact of the changes made. Since the model was put in use in 2010, McKesson has reduced its working capital by over $1 billion from improvements in its supply chain while improving its service in critical product areas.

 

Build direct integrated Google Analytics with AdWords account applied testing data to website design improvements. It also deployed campaign tagging and advanced segmentation to identify customer demographics. It used site overlay and funnel report insights to simplify purchase flow.

As a result there was an increase search conversions by 37%, email marketing conversion rate doubled and achieved 100% increase in sample orders.

 

CordMatch faced a challenge in using and implementing technology. They work to match cancer patients to cord-blood donors to retrieve stem cells for treatment.  So they wanted to create a modern, Internet-based matching system that is fast and easy to use. Integrate graph search and big data capabilities to rapidly compute data.

Solution was having CordMatch, an Internet-based donor matching system. Neo4j, a high-performance, enterprise-level graph database. A unique algorithm for a single and double cord searches.

The database enable blood banks, transplant centers and registries to communicate. Customizable search options simplify the matching of cord blood units. Uses a combination of innovative frameworks and a big data graph.

Hedgehog Insights- Data Don't Do

Why to analytics projects fail?

But that’s the story of less than half. Almost 55% of businesses implement big data analytics projects fails. They fail to arrive at the desired results.  Many do not why they started or what they were looking for from the analysis.  

An analytics project is  essentially a data  research project- and  like any other it is driven by objectives,  has (should have) a plan to put  to effect and should be  able to link expenditure  to tangible  business outcomes. But many miss a connection to objectives in the first place, let alone an execution plan to execute it. Following are some of the potential causes of failure as per our experience and research.

1.    Failing to build the need for big data within the organization

2.    Islands of analytics with “Excel culture”. Developing silo dashboards to answer a few questions rather than strategic, tactical and operational dashboards

3.    Lack of vision and not having a strategy; not having a clear organizational communications plan

4.    Lack of upfront planning; overlooking the development of governance and program oversight. Not establishing a formal training program

 

Which brings  us  to the  conclusion, that alone  analytics cannot lift the  dilapidated state of  affairs of  a business or  for  that matter  any  business requirement however, strong the need be or  however robust the analysis is. There has to be a full-fledged effort at an organization level built on a conviction that analytics can help and will help and it is absolutely necessary  teams follow a well baked execution plan to make that happen

About Hedgehog Insights– We are data analytics service provider . We offer analysis of business data. Be it daily operations, cash flows, website data or ones from social media, we analyze all of them together, on one platform, draw, connections, correlations, causes and offer our clients set of easily actionable insights. Tools are really in abundance and we are not selling another expensive one, all that we are sellingis a promise that our analysts will offermodern and conventional analytics , work with you and help you see hidden opportunities from your business data.Schedule a free consultation

What’s so Actionable about Actionable metrics?

One of the favorite buzzwords for analysts and data scientist today is ‘actionable metric’. Recently barged into the business lexicon and promising enough to find a long standing position this word hardly ever misses any sales pitch by any person in the business of analytics and data research.  Don’t try to connect to the meaning popular a decade back- here it’s nothing to do with law or criminal offense.

Actionable metrics are those that can be acted upon or used in business immediately, without making too many assumptions or help of a list of others – briefly, insightful information. The opposite of which is vanity metrics. Metrics that are remotely connected to use. Metrics, whose implications are subjected to the interpreter- meanings that differ from man to man.

Often we find web analytics that come with tons of metrics (and more being added even as speak), facing the fury of businesses- “too many dollar spent”, they call out  “and too little an information to use”. Agreed. Figures like number of clicks, number of visits, no. of exits or no of views are big pieces of junk. But so is sales if you did not know cost and cost if you had so information about revenue.

But if we measured count of clicks, over months, weeks, time of a day for posts to that blog you maintain, that could give great information. It could tell a reader’s preferences at various times of the year, hours when your audience are ready to read and time when you run the highest chance of  being in the limelight.

Thus it all comes down to the basis of analytics – contexts and comparisons. With right contexts in the backdrop and relevant comparison across every metric can be actionable or I’d prefer “intuitively informative”!

Since it is most popular among web analysts and Google Analytics as  the uncrowned king- lets just analyze how much action driven information this tool has  to offer.

Among the many types of analysis – dimension/metric combinations in  Google Analytics – We could count on just 5 as downright intuitively informative. They are unambiguous in their implication and pretty readily actionable (if that’s what we best understand)

Benchmarking- in Google Analytics

Bench-marking- in Google Analytics

Bench-marking Channels performance for Acquisition and Behavior- A new feature at Google Analytics and offers a comparative analysis of immediate industry in terms of channels used to acquire users and how they behave in each case.

Similar info is also available across geographic location. Important to note here is that, one gets to understand just which locations does that industry thrive in and sales or promotional channels most effective.

Cost Data- in Google Analytics

Cost Data- in Google Analytics

Cost to achieve goals- This involves uploading Cost data. Goals  achieved  is just as  good as the cost incurred –  be it micro or  macro . So all those signups, downloads, video watching or  purchase, how much did  it cost  advertising online or other , renovating the website  or to stock up that inventory etc.

Content Drilldown- in Google Analytics

Content Drilldown- in Google Analytics

Content drilldown and behavior metrics- Average  time spent on website gives a diluted idea of  engagement , but if you break it  down to each page  and  content level- that’s a solid  piece of  information giving exactly where  visitors  are engaged , if  at all.

It talks about just how good or relevant or engaging  is the content you have put out there.

Behavior- in Google Analytics

Behavior- in Google Analytics

Behaviors and rate of goal conversion across channels- Your bounce rates, page depth, and pages visited can be broken down to channels and within channels, different social platforms, referring websites or keywords that direct organic search traffic.  Is there a correlative movement between the behavior metrics and channels or sources that send. Is there any tips about where they found your link and how far is it  relevant  to that context?

Drill  it down and you’ll see somewhere it relates  to channel performance and effectiveness of all your resource , time  money and energy spent in there.

SEO Queries- in Google Analytics

SEO Queries- in Google Analytics

Queries in Search Engine Optimizations and Resultant movement over period- One of the  best form of  information available on the tool is what queries in  search gives what result- is  your website search engine optimized, where  does  your page rank for  searches  you love and

Conclusion- Metrics vary in the depth of  intuitive and  actionable  quality , but a lot of  it  depends  on the analysis it  self and of course skills of a seasoned  analyst.  If  you do not  have an analyst  or  new  to this as a business  owner, remember  it is important , the way  data is viewed and the context it is put up against. Instead  of viewing data singularly  or as a mass of aggregates, slice it  down and  try al types of  comparisons. Some will turn out meaningless but many will become insightful. Believe it  or that’s  how all analysts start! Good Luck.

About Hedgehog Insights– We are data analytics service provider . We offer analysis of business data. Be it daily operations, cash flows, website data or ones from social media, we analyze all of them together, on one platform, draw, connections, correlations, causes and offer our clients set of easily actionable insights. Tools are really in abundance and we are not selling another expensive one, all that we are sellingis a promise that our analysts will offermodern and conventional analytics , work with you and help you see hidden opportunities from your business data.Schedule a free consultation