We don’t need to get new customers!

Published March 10, 2010 by John Maller
We don’t need to get new customers!

We don’t need to get new customers!

Very bold statement from the Macy’s CMO Peter Sachse in his keynote speech at the Retail Innovation & Marketing Conference talking about a shift in company focus.

Here’s how it all started: Last year, Macy’s embarked on an intense research project to better understand their current customers. They conducted dozens of focus groups. Talked with nearly a thousand people walking out of their stores. Leveraged data from NPD Group for a holistic understanding of their customers. Combed through all of their transactional data to find themes in buying patterns and shopping habits.

The overwhelming finding?  For Macy’s, “What we don’t need to do is get new customers,” Sachse said. Instead, “we realized that all we need to do is take care of those who already love us.”

The company has set out on a goal to encourage each existing customers to visit the store one more time each year. “Half the battle is won if we can get them to walk into our store,” Sachse said. “And if we convert them during that visit, our comp store sales will explode.” To accomplish that goal, he said, “We had to get a lot closer to the customer,” which has led to the company’s new strategy of customer-centricity.

I could not agree more! Macy’s needs to understand the buying patterns of its current customers and serve them better. This will result in higher customer satisfaction, higher repeat sales and higher profits. If you do not know the buying patterns of your current customers, getting more customers is NOT going to help. Mr Sachse is absolutely right!

Companies today spend tons of money trying to get more customers. Very few companies have a finger on the pulse of the buying patterns and trends of their current customers.   What is the point of getting more customers if you cannot serve the one that you already have? Is it just busy work? Or is it because with thousands of SKUs, companies do not know how to keep up with customer buying patterns?

Congratulations Mr Sachse! I look forward to walking into your store and finding the right stuff.

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A Race Towards Pervasive Analytics

Published March 8, 2010 by John Maller

Gartner’s top 10 trends for 2010 set the stage for Cloud computing and Analytics.

Analytics is context driven, and presents actionable results to the business user. BI allows the user to slice and dice data. BI is good if you know what you are looking for. The reason Gartner placed analytics above BI is because of the needs of businesses today to act on data, as opposed to merely having access to it.  There is way too much data. We do not need systems that create more data - we need intelligence from the data, which is what Analytics does. Hence the positioning of Analytics on the Gartner charts.

BI has become pervasive, as it should be. It has even entered open source with Pentaho and Jaspersoft, a sure sign of being pervasive!  However, this was inevitable as every business user needs easy access to their data. A recent survey conducted by B Eye Network involving more than 1,000 respondents from around the globe found that only 12 percent said they had no plans to use open source software in some form for business intelligence applications or data warehouses.

However – converting the data to intelligence, and actionable intelligence in the next frontier. That is why Gartner placed Analytics in their top 10 trends chart, and moved BI out! As we have watched with Google analytics, the analytics on web traffic data is pervasive. There are a myriad of products that provide analytics on web stats, but Google provides a universal product ensuring that everyone has access to it.

Analytics on corporate data will also become pervasive. Companies are demanding this. The analytics will be contextual, as this is required for analytics to automatically make sense out of data. The analytics will be agile and companies will be able to pour their data in, and watch the results take shape. Much like Google analytics on web traffic data.

Emcien’s analytics offers analytics on sales data.  The context is sales and customer buying patterns. Companies can now pour the sales data and watch the customer buying patterns emerge. No data mapping and model building.  No long implementation cycles! The ability to “just turn on and use” is key to being pervasive.

The future is here!

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Why the need for Intuitive analytics?

Published February 22, 2010 by John Maller

I just finished meeting with Kathy, a customer who is very analytical and has done an amazing job delivering value on data intelligence for her company. I spend an hour with her and she described the process of implementing tools to gain value from data.  “This has been a painful process of exploration” she said. “We are a team of analytical types, and we love to play in the data. Not all companies can afford a team like this.  In my last company we could not afford it. And companies cannot compete effectively if they cannot gain intelligence from their data!”

I asked her the challenges with the project and lessons learned. Kathy is a data genius, and there are very few folks like her. Here are some of the points that she made.

  1. “What am I supposed to do?” The analytics tool needs to answer this question for the business user. It also needs to be very easy to use and understand.   This comment reminded me of another conversation with a BI user, and his pet peeves with his BI tools - “I do not know what question to ask!” He said. “Asking intelligent questions is most of the task!”
  2. Tools for Business Users. Not R&D. Not IT. Kathy went on to comment about the dire need for tools for the Business Users. Companies are running very lean. The last rounds of corporate downsizing have been brutal. Typically, the first teams to go are the analysts and R&D teams. Hence, if the tools are hard to use, now they will never get used. Business leaders are getting smart and they want tools that their line-of-business folks can use. This can help them get value in the line of business.
  3. Actionable Results. The old slice-and-dice data capability is not useful.  Ask may questions and I will answer. The business units are too busy and do not have time to “play in the data”. The tools need to intuitive and give you actionable tasks.
  4. Like Google Analytics - The words “Analytics” is always associated with webs stats. That is the most commonly understood context of the word. However, there is far more data residing and building up in companies, than there is web traffic and search strings data. We need the same level of analytics, easy to use and intuitive tools for corporate data as we have for the web stats. Analytics means computing a relevant result and presenting easy to understand solutions. Like Google analytics for web traffic. Google analytics presents analytics on web stats; very domain specific, turn it on and off you go! Analytics for companies needs to be like that. Domain specific. Turn it on. Go Live. Get results. Get value!
  5. Need to think like B2C apps. This was an important point. Why do business users have ugly, clunky software that is expensive to implement and difficult to use?  How can they be effective making those million dollar decisions? When the new wave of kids, who grew up with iPods and Facebook, enter the work force, will they throw out all the clunky enterprise apps? Absolutely!! Replace them with with easy to use, Facebook like apps.  Business analytics needs to be that easy to use.

Great opportunities! We need to build applications with the user in mind. What will business applications learn from iPod, Facebook, Linkedin, ……

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BI is for IT, But Analytics is for the Business User!

Published February 16, 2010 by John Maller

I’ve just come out of a meeting with a business user who is passing up on a well-known BI software package. “It takes too many IT resources to implement. My IT guys love it but I cannot afford the cost/time,” he said.

As companies drown in data, BI is a very expensive route to try and gain value from the data. Mark McDonald, head of research for Gartner Executive Programs, has a very nice article titled Without the Business in Business Intelligence, BI is Dead!. Sounds like – “The King is Dead. Long Live the King.”

BI has been built for the IT community. It is an old-school solution built on the heavy weight model of technology. That model rests on the acquisition, installation and operation of technology based on a significant upfront investment that is earned out over a period of time. This has been the investment/implementation path for enterprise ERP/SCM/CRM/PDM software packages. BI is in this class of software solutions, and results in an expensive and less responsive solution.  Mark McDonald calls this the “old ‘heavy weight’ model of technology”.

The top two categories for Gartner’s predictions for 2010 are Cloud Computing and Analytics – these are both directions that are a far cry from the old world of heavy/expensive/pay upfront software. BI in its current form is completely out of step with these predictions and where the market is heading. So, why did Gartner renamed BI to Analytics? In doing so is BI going to magically transform from its old heavy weight form to a new lean enterprise 2.0 form? Long Live the King?

Emcien offers pattern-based analytics that easily takes sales data in any form to reveal customer buying patterns and trends.  The technology has completely eliminated the need for data models, structures, mapping, etc. Emcien’s pattern based analytics technology was created explicitly to overcome the ‘old heavy weight model of technology’. Pour your sales data in, and watch the customer buying patterns. “Like Google analytics for sales data”, our customers told us.

Mark McDonald has prophecy for BI that I think is dead-on (pun!?). “On a radical note, we are seeing some early signs that companies are looking to use social media/web 2.0 technologies to address business issues that were previously assigned to BI.

Lighter weight technologies handle tacit information and semi-structured process support better than BI solutions that rely on structured and standardized information.

Lighter weight technologies handle tacit information and semi-structured process support better than BI solutions that rely on structured and standardized information.

Our customers completely agree with Mark McDonald. Quoting a VP from a Fortune 500 company, “We have lost the appetite for million dollar software and long implementations that consume IT resources”.

However, the need for harvesting intelligence from data is not going away. On the contrary, it has never been more important than it is now. The data hides jewels of intelligence that companies need to act on NOW. But that is only possible if Business Intelligence is not a technology but a capability for the enterprise. Long Live the King!

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Demand Intelligence Among IDC’s Top 10 Retail Predictions

Published February 4, 2010 by John Maller

Just read a great article by Amanda Ferrante based on an interview of  Leslie Hand, Research Director at IDC Retail Insights for Retail Touchpoints. The interview focused on providing new strategies to optimize the value of IT in 2010, as IDC Retail Insights unveiled its Top 10 Predictions for the retail industry. The IDC report explored several hot retail topics, including social commerce, mobility and how demand intelligence is driving inventory management.

In the interview for Retail TouchPoints Leslie expanded on the IDC predictions. The first set of points were around the impact of social networks and it sizeable impact in retail.  Everyone is talking about social networks, and we all know it is like the iceberg that sank the Titanic. We see a small piece and there is a big chunk underwater! (bad analogy!) But no ones knows the true financial value of this. I guess the analysts counsel is to chase this bubble it and stay on top of it, so that when folks figure out how to monetize it, you are positioned well.  Just hope that we are not standing there with a load of tulip bulbs!

The interview mentions Demand Intelligence as being critical. Leslie says that retailers with capabilities for sensing demand were able to fine tune assortments, reduce demand forecasts and adjust prices and promotional programs to maintain margin expectations given expected product sell-through issues. On the flip side, many retailers were left holding the bag, as they did NOT have the capabilities to adjust to the changes. As consumer spending shifts and demand fluctuations grow, Demand Intelligence is mandatory to run a a profitable business.

In Leslie’s words “Many of the retailers who were not able to adjust expectations soon enough, because of the timeliness of demand data or insufficient analytics, remedied the situation by investing in better forecasting and planning tools in 2009. Part of the success this past holiday season can be attributed to merchants sticking to the plan, with an understanding that the data and the analytics and planning tools that were used to develop the plan were smarter and more agile than human experience alone. We believe this was a tipping point for many retailers, who may not have been fully invested in demand intelligence before.”

The predictions also touch on the importance and trends of mobile applications, and connecting customer behavior and purchase data for more insight.   However, to me, the second one sounds like lots of data, long implementations, ……

On that note, I would like to add that a key factor for applications to be successful in this economy is quick proof points and fast implementation. As competition heats up even more, retailers needs tools that can quickly demonstrate proof points and deliver value.  Solution providers and software vendors need the capability to quickly implement their solutions, without lengthy and costly  implementation cycles. This is even more important for the small and medium retailers.   I guess the bigger guys would say … why leave me out!  :))

[J86ZEDNBT7UH]

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Making Analytics Actionable

Published February 2, 2010 by John Maller

I just read an article titled “Making Analytics Actionable” by Michael Vizard. He makes two good points – predictive analytics is not new and analytics needs to be actionable. I could not agree more.

On the first – predictive analytics has been around for a long time. We used to call it forecasting. It was difficult then, and it is difficult now. Forecasting gurus, or should I say Predictive Analytics gurus have thrown every mathematical trick at the data to predict the future. It reminds of a quote by the CEO of a Fortune 500 company, who said “No one knows how to forecast. If they did, they would be in a different business.” I think by different business he meant forecasting money on Wall Street. But we all know that has gone! And now may be the quants on Wall Street would agree with him as well.

On the second point – yes, analytics should give you actionable information. As I hear from our customers, time and time again, they do not need more data. Companies are drowning downing in data.  (maybe “downing” is the right word!!! We are downing in data! It is a downer!!!) In the name of Business Intelligence, they now have the capability to slice and dice this data, creating more data! The purpose of analytics is to convert all that data into something meaningful and actionable. If the analytics does not accomplish that, it is just another BI tool.

As you investigate analytics for your business, here are a few best practices:

  1. The analytics need to be focused by business function.
  2. The analytics needs to answer the question “What do I do with this?” and “what is the business value”.
  3. The analytics should make your job easier, and the recommendations should want you coming back to it over and over again.

The answer to the question “What do I do with this?” should be actionable tasks that a business should be able to run with. That is called Business Analytics.  The reason the third point exists is because you, the user, would only come back to it over and over again if it made your job easier. That is the key to business analytics. “Take all that data and convert it into actionable tasks and make your job easier”. How is that for a tag line!

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Revealing Patterns of Change

Published January 25, 2010 by John Maller
This is Fun, But Not When You Are Under the Gun!!!

This is Fun, But Not When You Are Under the Gun!!!

Gartner has launched a new focus area called “Pattern Based Strategy”, based on the need of businesses to capitalize on large amounts of data and the new rules for business process adaptation.

Here is a great verbatim quote from the Gartner web page.
The depth of the recent recession blindsided most businesses. As the economy starts to recover, many business leaders are thinking, “If I had seen this coming sooner, I could have acted faster, decreased my risk and enhanced my opportunities for growth.” There is a way to see things coming. It’s a framework for proactively seeking and acting on the early and often-termed “weak” signals forming patterns in the marketplace. It’s also about the ability to model the impact of patterns on your organization and identify the disciplines and technologies that help you consistently adapt. It’s called Pattern-Based Strategy.

The key to Pattern Based Strategy is automatically revealing intelligence that is hidden in the data/information.  Companies today are running more lean than ever before. Employees across all organizations are inundated with work and overloaded with data. .   There is a great need for technology that will make our jobs easier and make us more productive. At Gartner, the idea that emerged, led by Yvonne Genovese, is called Pattern-based Strategy (PBS).

We are victims of too much information, missed opportunities and ‘@#$% I wish I could have seen that!‘ moments. Connecting this to a rather timely/charged topic - Think about a recent attempted terrorist attack by the Nigerian traveler who bought a one-way ticket,  paid in cash, checked no bags, boarded an international plane. There were a very large number of ‘red flags’ in the sequence of events, and there was a large volume of data hiding all this intelligence. A Hope Strategy is to hire tons of people and make them search the data for red flags, more importantly sequences of red flags.  This may work sometimes. But it is a poor and expensive strategy, and rarely does it produce the desired results on time! (making it quite useless, actually!)

As companies start to incorporate intelligence from data into their operations, one of the primary issues is the ability to have the intelligence automatically come to you. ‘Digging for insight’ is a poor, time consuming, expensive strategy.   We need the technology to work for us.  Second, it is also important to start focusing the insight with a particular business function/strategy in mind. Sales, Marketing, Operations, etc.

Connecting this back to what we do, Emcien provides analytics that automatically reveal customer buying patterns in sales data. The analytics reveals the popular choice combinations, key differences by region, key trends and new emerging segments.  This is an example of technology working for you, bringing insights back so that you can act on it.

Quoting a Regional Practice Manager and the Senior Architect for Siebel -
 Emcien offers rigorous and repeatable detection of buying patterns, enabling your customers to act on them, while supporting your product objectives (margin, inventory, velocity, …)

Quoting a former Oracle Practice Manager and Senior Siebel Architect -
Emcien offers rigorous and repeatable detection of buying patterns, enabling your customers to act on them, while supporting your product objectives (margin, inventory, velocity, …). Emcien’s offerings readily integrate with Siebel, enabling immediate improvements to revenues.  Few projects offer such potential for improving the customer experience and increasing revenues, with so relatively little development or integration efforts.

Automatically revealing patterns is required today as we all drown in data, and do not have time to hope that someone may find the intelligence that the organization needs to act on. Thanks to Gartner for launching this focus area!

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Increase Sales With Analytics on Sales Receipts

Published December 28, 2009 by John Maller
Increase Sales with Purposeful Analytics On Sales Receipts

Increase Sales with Purposeful Analytics On Sales Receipts

The sales receipt is a neatly itemized list of purchases.  Every purchase comes with a specific need, and hence the sales receipt is the true voice of the customer. As demand patterns change, the sales receipt data can reveal tremendous intelligence on what customers are buying, the changing trends and what the future purchases will be. “Stores Face New Kind of Shopper” is a very interesting article by Ann Zimmerman and Rachel Dodes in The Wall Street Journal (Monday, December 28th 2009).

The financial crisis has dramatically impacted sales in all markets. Over the last two years sales have plummeted, consumers have disappeared and profits have evaporated. The financial crisis has caught us in a time of tremendous over capacity. In the B2B markets, companies have been dramatically shrinking capacity to match the new level of demand. In B2C markets, retail experts generally believe that the US now has more stores than consumer demand can support.

Customer buying patterns are dramatically changing as capacity adjusts to the new level of demand. The financial downturn further impacts this change, as customers look for new ways to stretch their money. To complicate things further, customers today have many choices of products, channels and price point.   The internet has become a primary source for browsing and comparison shopping.   This extends the reach of the customers, and puts pressure on companies to cater to wider product choice selection. As these shifts continue to change buying behavior, companies must have the capabilities to stay ahead of the changes. With the speed of change in products, companies need to adapt fast and stay in tune with changing demand.

The good news is that the sales receipts reveal these changing trends and buying patterns. However, this requires purposeful analytics designed to convert sales data into actionable tasks. I would also like to mention that sales data has a unique structure and characteristics. The purpose of the analytics is to reverse engineer the sales data to determine what is selling. If your product has a lot of feature choices, you can get insight into the popular choice combinations. If you sell lots of individual items (i.e. large number of SKU’s), you can get insight into what are items that are commonly grouped together. Emcien offers analytics designed for sales data. Emcien’s advanced analytics cal also give you intelligence into what choices cause the selection of other choices. Armed with this insight, you can manage your product offering to always stay ahead of the trends.

With purposeful analytics designed for sales data, you can get insight into -

  • What product choice combinations are popular?
  • How do the choice combinations vary by channel?
  • What choice combinations are profitable?
  • What are the changing trends and what choices will sell in the future?

As the market shift continues, this level of demand intelligence is mandatory to stay profitable!

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How Good Is Your Demand Intelligence?

Published December 18, 2009 by John Maller

I was meeting with Martin, the CEO of a fortune 1000 Company.  He talked about sales productivity as a significant opportunity and an area of strategic focus for 2010.  “We have been selling this product for years. Yet, every day is ground hog’s day for our sales reps. What I mean by that is every sales call and quote request is treated as if we have never sold this product before!”.

Maximize Sales Productivity On Every Channel With Demand Intelligence

Maximize Sales Productivity On Every Channel With Demand Intelligence

In the B2B markets there are distinctive patterns in the product choices that customers make. It isn’t really customer intelligence as much as demand intelligence. The B2B markets are different from B2C. The average purchase value is typically larger, the frequency of the same end-customer is lower, but there are distinctive patterns in the product purchases. The purchase patterns exist by product choice combinations, customer type, vertical, usage, geographic region, price point and so on.

“I know that there are patterns in what our customers buy,” added Martin. He was previously the VP of Sales and has knowledge of what products customers buy. “We need our sales reps to have access to that intelligence so that they can be better advisors to customers and close the deal faster.  I have sat in sales meetings with a company exactly like the one we sold to 3 months ago, and watched my sales rep grill the prospect on product requirements. That hurts our sales more than anything else.”

In a recent blog, Michael Gerard from IDC wrote a very interesting article on the same topic. He mentions a story where a CIO from a $10B+ company had to continuously teach a vendor sales reps what he had purchased from them in the past. The article goes on to state that this can lead to poor credibility on the sales front lines.

There is a solution for this problem. Every company is sitting on tons of sales data. It is a wealth of data that can reveal what their customers are buying and where they are willing to spend their money. Emcien offers analytics that auto-detects the choice combinations in sales data. What are they buying? What are popular product choice combinations? What are popular choice combinations by vertical? What combinations are profitable? Which ones are not?  This is the demand intelligence that makes each day NOT be ground hog’s day!!

As a first step, it is invaluable to arm your sales reps with this intelligence so that they can be smart on every deal. In fact, every sales channel can benefit from this intelligence. Here are a few examples -

  • Sales reps can use demand intelligence to be better advisors to customers, convert requests to quotes faster and recommend good choices to close the deal. Even a simple report on what is the fastest selling product choices will empower your sales reps, and drive to the bottom line.
  • Your ecommerce site can use demand intelligence to quickly recommend the best products to help the customers to self-serve on and make better decisions.
  • Inside sales team can use demand intelligence to quickly complete quotes and close the deal.  I was talking to an inside sales rep and he told me that his biggest challenge is quickly responding to a quote with a price.  ”We have done this so many times before,” he said. “Why does it take us to long to get a price?  We lose deals because we cannot respond fast. The first to respond with a quote locks in the deal 90% of the times, even if the price is higher. We lose deals by being slow.”
  • Call centers can use demand intelligence to cross sell/up sell based on buying patterns. The turn over in call centers is high. Automating the cross/up sell with demand intelligence will dramatically improve productivity and profit.

Quoting Michael Gerard “This is only the tip of the iceberg of course.” Demand intelligence can dramatically improve your sales performance, customer satisfaction and profit margins.

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Gartner: Cloud computing, Analytics Top 2010 Strategic Tech List …

Published December 14, 2009 by John Maller

Cloud computing and analytics have jumped front and center. Gartner renamed Business Intelligence (BI) to Analytics.

On the analytics front, Gartner said in a presentation: “We have reached the point in the improvement of performance and costs that we can afford to perform analytics and simulation for each and every action taken in the business. Not only will data center systems be able to do this, but mobile devices will have access to data and enough capability to perform analytics themselves, potentially enabling use of optimization and simulation everywhere and every time. This can be viewed as a third step in supporting operational business decisions.”

Analytics Named as the #2 most important category, behind Cloud Computing

Analytics named as the #2 most important category, behind Cloud Computing

Gartner names analytics as the #2 most important category, only behind Cloud Computing. Analytics is becoming more important to all aspects of every business.

So what is analytics? It is purposeful focus on data. It requires mathematical analysis and algorithms on data, to compute Key Performance Indicators (KPI) that are valuable to measure the condition of the business.

Emcien offers analytics to detect product-buying patters with a focus to improve product mix and profitability. As product choices and market segments have grown to dizzying levels, companies struggle to have a finger on the pulse of their product mix, markets and profitability. What products are making money? What are customers buying? What are popular choice combinations? What is common across the market segments? What are the trends by market segment? What product choices should we offer?

Emcien’s analytics answers these questions with patented mathematical algorithms applied to sales data. Emcien’s analytics auto-detects what choices combinations customers are buying, the trends and which choice combinations are profitable. The product offering is the lifeblood of a company. At Emcien we equate product mix and choice mix to profit.  If your product mix is not aligned with what customers are buying, you will not make profits.  It is as simple as that!

Emcien’s analytics is built on sales data. Unlike web analytics, where is data is a bear, getting sales data is a relatively easy. This is usually the best quality data compared to anything else. The sales data is a true capture of the voice of the customer. It allows companies to see what customers are spending their money on. The value of Emcien’s analytics is visibility into customer choices, and more importantly, recommendations to increase profitability.

Analytics are very powerful as the data reveals Key Performance Indicators that offer continuous insight into the business. You can dispel a lot of beliefs that the company has based on gut feel and cooler talk. When you provide actual sales data driven insight, it has a profound positive impact on the company and the decisions. To convert analytics to action select KPI’s that are a part of your business process and budgeting process. This is key to showing improvement that is meaningful to the organization. As analytics gets more visibility in the C-suite, there is demand to produce KPIs that executives are measured on. This will help gain buy-in at executive levels as adoption of analytics grows.

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