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7 Items your Business Needs to consider, to Influence Customer Buying Behaviour?

People – Process – Data – Domain Knowledge – Technology – Analytics – Plan

The above 7 items is all you need. But I would like to start off by saying that:

“Every Business is unique! Every business has its own leadership, Culture, Products, Pricing, Marketing, Customers, Technology, Processes, Analytics”.

It therefore makes sense to acknowledge that every business has it’s own needs, it’s own business questions that need to be answered at any specific point in time. Questions such as Which of our customers are buying product A, How can we increase our number of customers by 20%, How do most of our customers buy from us, What is the customer process for buying our products, When can we expect our customers to change their buying behaviour, How can we reduce churn?

Your data can answer all these questions. You may have several sources of data such as

  • Descriptive – demographic, geographic,
  • Attitudinal – preferences, needs,
  • Interaction – Email, web, call centres
  • Behavioural – transactions, payment history, usage
  • Website Activity – Number of customers, Number of conversions,
  • Social Media – Positive Sentiments versus Negative Sentiments

To influence your customer behaviour, that is, to get customers to do what you want them to do, your business needs the right People, the right Processes and the right Plan in place. Talking to your business domain experts and then taking the relevant data necessary to answer your business question through the use of technology and tools such as SPSS, SAS, R, etc businesses can uncover key insights that will greatly assist them with proactive decision making and business strategy.

Now, what do I mean by the right People? The right people refers to the right employees and the right customers. Having the right employees, means that your business must have the right talent who have enough experience in the industry and with your products as well as the right analytic skill set to better understand the data and how to derive business insights from it.

Having the right customers, means that your business understands exactly who are their target customers, what they like, what they dislike, what they perceive as being most important and what are their current needs.

Having the Right Processes in place, is all about having processes in place at each of the customer touch points where by your business can engage or incentivise your customers to buy your product or service and integrate all the data from a single customer as a single view. This is where the power of the analytics lie. By integrating all you know about your customers into one file, you are able to determine relationships between different customer activities that allow you to make offers or to the right customer, at the right time with the right product offer using the right channel.

What about the Right Plan. How does your ensure that they have the Right Plan? I wold say, it all about the 7 items that your business needs to consider and taking each of them into account, your analyst will have enough information to decide how best to answer the business questions. Based on the business question, your analyst will identify the best statistical techniques and tools that need to be used to provide your business with accurate and reliable results to strategy and proactive decide on what is the best approach to successfully achieve the business goal.

Please share any questions you may have at this point…I will follow on from here next time with some common business questions and the statistical technique and approach that may be used.

Big Data – Data is now an Asset and can even be a Gold Mine – But only so, if Analysed & used timely!

What is all the fuss about Big Data? Everyone is talking about Big Data, Hadoop, Map Reduce, etc

 

Let me tell you, you can have all the data in the world at your finger tips but it doesn’t mean anything, if all you do is store it. And, that is a costly affair and a big waste of time, money and lost opportunities of owning a gold mine!

 

There are many examples, of use cases, how many businesses have used their data to make decisions faster (almost real time), smarter (not gut feel, but listening to the data & what it is telling you) and timely (data also has a use by date)!

 

Using statistical techniques, we are able to run algorithms that identify patterns in the huge data sets. These patterns help businesses identify insights that allow for smarter, faster, timely decisions!. For example, Google used search terms by region in the United States to predict flu outbreaks faster than was possible using hospital data.

 

Other examples, using sensor data from ships, you are able to build statistical models that will predict more accurately when a ship needs to be serviced or repaired at the right time (instead of calendar days) based on the engine (heat, vibration, sounds, age, engine type, number of gears, gear type, distance travelled, average speed, etc). Statistical models can identify which ships will need to serviced, together with the probability of the engine failing. Using this information, Big Data Analytics will save the business lots of money as the service will be cheaper than actually repairing the ship engine once it fails. By preventing a ship from breaking down, Big Data Analytics will save the business millions of dollars as there will be less delay (repair time is longer and more costly than service time) in doing business as usual. A shipping business can reduce total repair time and reduce costs of repair. 

 

Building a business intelligence system is the first step in better understanding Big Data. A business intelligence system is typically, a dashboard which displays bar charts, pie charts, trend plots, and these days are highly interactive and can tell a story in a few minutes. Data Visualization is key! It is your starting point to understanding key variables and metrics related to your business profitability and Return on Investment. One thing, whatever you decide to have on your dashboard, make sure it delivers actionable insights. Which means if the “traffic light system is red, the business user needs to know what to do versus if the traffic light system is green”. Many businesses are developing creative ways in visualizing their data and are making it much easier for the  user to see and understand the patterns instead of complex model outputs and formulas.

 

Big Data Analytics can also help transport related organisations where the next accident is likely to take place and the probability of the accident occurring. This is very useful, as the police, ambulance, fire brigade, re-routing systems can all proactively make decisions based on the information provided by Big Data Analytics. The result being the police, fire brigade, ambulance, etc can strategically position themselves so that they are more likely to be at the right place, at the right time, so that the incident is cleared quicker, the patients are transported more quickly to the hospital and the traffic jam is cleared more quickly. The amount of money that is saved by using Big Data Analytics is massive. The amount of lives that can be saved, because of the use of Big Data Analytics is also big.

 

So, I can go on and on sharing many examples but I guess the question that needs to be answered is “Where do you start?”

I recommend taking an agile approach. Start with a business problem, one whose solution is  achieveable in a reasonable space of time. Start small, “like a baby just born and take baby steps, with your mother (someone with experience and the expertise, who knows better) to help you along the way. Yes, you may fall as you take your first steps, everyone falls, it is okay. Get up and soon you will be waling confidently, and then running and enjoying the data mining. Like mining gold as you see the benefits reap!

 

Please let me know if you have any questions on Big Data Analytics….its not easy to cover everything here!

 

Supply Chain Analytics – How can it help you?

Supply chain analytics helps you to better understand your business processes end to end. Many organisations in the supply chain industry have lots of data but are not making good use of it. By applying statistical techniques and analysing your data you can certainly make better decisions based on what has happened in the past, and based on what is currently happening, and based on what is likely to happen in the future.

 

By drawing a diagram that footprints your process from the raw ingredient selection  – to the distribution to the machine at the manufacturing factory  – to the employee working at the machine  – to the quality test – to distribution to the inventory warehouse – distribution to the retail store – to the back office – shelf- teller – transport – customer. Easily more than 10 processes.

 

As a start, visualization is the best starting point. Simple plots such as bar charts, trend charts, box plots and pie charts of the average time, minimum time, maximum time, standard deviation, time between events, can easily help businesses better understand what has happened. 

 

But the power of supply chain analytics is in what is likely to happen. Knowing this, gives a business the power and time to be proactive and innovatively decide on what to do, based on the forecasts, This will give your business an advantage to differentiate itself from its competition and thereby gain a competitive advantage. 

 

Forecasting models can easily be automated using statistical modelling techniques and deploying these models into the business operations. But it is important that once these forecasting models are deployed in the operating system, they should be monitored and over time, alerts should also be placed in the operating system when there is a change in the direction of the activity or when the quality of a product is below required standards, the machine operator should be alerted.

It is important that operational analytics are shared among all the stakeholders and departments so that all parties have almost real time information and this will allow the whole company to make proactive decisions always using the latest information. This means that better decisions will be made as they are based on the latest data which is the most accurate information.

 

Supply chain forecasts also allow a business to plan more effectively. Once the forecasting models are built, what if scenarios may be used to compare and adjust the forecasts based on your business goals and constraints.

Using real time insights businesses will be alerted to when they are overstocking or under-stocking, and thereby help businesses to make adjustments early and avoid loss in sales. These overstocking and under-stocking insights can contribute to tremendous savings for the business, which means increased return on investment. And, that is usually the goal of the business…increased return on investments!

 

Not sure, if I have convinced you enough that measuring and analysing your supply chain data helps you to make decisions faster, smarter and at the right time. Timing is the essence and the key to improving your supply chain operations.

Of course, there is much more that I can discuss here. But, please let me know if you have any questions.

What do Businesses Do with Their Data?

Collecting Data is easy…but applying analytics to better understand customer needs and wants is not so easy! It all boils down to what valuable information you need to better understand your customer. There is so much data that you earn, accompanied by data available from the outside, so a right balance needs to be struck! You need to find what really works for you, if not, you will possibly be caught in information overloading with Big Data accumulation.

 

Supermarkets are combining their loyalty card data with social media information to detect and leverage changing buying patterns. For example, it is easy for retailers to predict that a woman is pregnant simply based on the changing buying patterns. This allows them to target pregnant women with promotions for baby related goods.

 

Grocery Data – Customers usually buy steak, and are now buying hamburgers. They are also now buying with more coupons….This says a lot! Data can be very meaningful if used smartly! Collect data wisely, collect data when you have a good idea why you are collecting it and how you will use it. Using this data and combining insights can be very powerful. Using the above information, a retailer will be aware that the economy is in a down market and this will alert him to allow more promotions on steaks to boost the sales of steaks and to reduce the amount of steaks on the shelf until the economy is up again.

 

Many businesses collect data and do absolutely nothing with it, except store it! The data does not actually inform the business. Others, spend lots of time collecting the data, cleaning the data, and then produce beautiful charts and summary statistic tables for their regular reports and or dashboards, but that is as far as it goes…  If sales has dropped from one month to another, then the dashboard will display the drop using a bar chart or trend graph. But that is not good enough. The business should ask itself many more questions. Questions such as: Why has the sales dropped? Which products have dropped in sales? Which sales people have dropped in their sales? Which stores have dropped in sales? Which regions have dropped in sales? Which sales channel has dropped in sales?  And most importantly, what should the business do???

 

By answering the above series of questions, the business will find insights/golden nuggets that will inform the business as to the cause in the drop in sales. Based on these causes, the business will have to take the necessary steps to bring back the sales to an acceptable or increasing level.

 

Businesses need to develop dashboards that help them in their day to day business decisions. Always let the data speak to you, let it tell you what to do. Gone are the days when decisions were randomly made without any evidence or data!

 

Do let me know if you have any questions regarding the collection of data. Why do you collect it? And, when and how do you use your data.