InetSoft Product Information: Incorporating Web Analytics into a Business Intelligence Solution

Looking a business intelligence solution that can incorporate Web site analytics? InetSoft offers a Web-based BI platform that can mashup disparate data sources including Web site logs or data from a Web analytics API. Read articles below about InetSoft's BI and Analytics Solution.

Example for Marketing Analysis - The second example was for marketing analysis in the field for very large automobile manufacturer. Their big objective as a company was to change their relationships with the dealers. Become more consultative with the dealers, more consultative in terms of what’s selling, what kinds of promotions work on which vehicles. Going down to the vehicle level, in fact even down to the version of those vehicles, including discounts on after market parts. The company wanted to push profit and loss responsibility down to the regional level and to do that the company had to provide regional sales managers with much greater visibility and much greater ability to explore their data. Sales reps and managers are able to quickly ask entirely new questions with an interface that has this walkup usability, and it actually gives them a greater ability to consult with the folks who run the dealerships themselves. We did a similar thing with another customer, a company that sells seeds, many different kinds of seeds. They have different properties engineered into the seeds, and this company uses test beds all over the country so that they can get really good data on the yield that different kinds of seed produce in different kinds of soil at different kinds of latitude...

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Examples of Companies Using Analytic Scorecards - For example, a pharmaceutical company is trying to measure the relationship they have with key thought leaders and doctors. So they have a thought leader engagement index, they call it. They identify within each field who are the big thought leaders, who are people writing the books, writing the papers or are influential over other doctors and other academics. They’ve identified these top 15 or 20 people around the world, and then they measured the relationship they have with them. The highest level of relationship might be a doctor that will go to seminars for you and talk about the wonders of your product to other doctors. You’ve been working together for years and they have total trusting, friendly type relationship. Another doctor might be one that won’t even give you an appointment, and you’re still just communicating through emails and phone calls, and so you have the beginnings of a relationship there, but maybe they don’t trust your pharmaceutical company, and they’ve had bad relationships with you before, and so that would be an example of somebody you’re trying to get a first date with whereas the other one would be like a marriage...

Exploration and Analysis - With exploration and analysis we are really navigating through historical sets of data. It’s much more of a top-down type of analysis where we see the results. And then we have a hypothesis, a mental-model of perhaps of what caused that result, and then we go explore the data, drill-down to hierarchies across dimensions to find the root cause. So in that respect it is very deductive type of reasoning that we employ in that type of analysis. But, typically we are using query tools and OLAP tools to do that type of analysis...

Four Types of Analysts - All right, so let’s meet your analysts. There are four types of analysts out there, and they have labels: “Super User”, “Business Analyst”, “Analytical Modeler”, and “Business Manager.” Super User, he is a business guy in sales, or marketing, or finance who has gravitated toward the technology, finds that he likes using Excel or the BI tools, likes building reports and rolling up his sleeves and wading into the data. And over time he has become the go-to guy for everyone in the department to build ad hoc reports or ad hoc views of information. He may not have report creation and design as part of his job description, but this is something that he had carved out a reputation doing. Next is the “Business Analyst” who was hired to crunch data on a day-to-day basis. She probably has an MBA, probably very good Excel skills, Access skills, may know a little bit of SAS, SPSS. She probably has a title of Financial Analyst, or Marketing Analyst, or Sales and Operations Analyst, and plays a lot of different roles within the organization...

Good Customer Analytics - Customer analytics helps transform your data into something usable in day to day business. Good customer analytics becomes a powerful marketing tool used to jump hurdles and transform them into successful vantage points. Businesses accumulate data as they operate; customer information, sales numbers, employee salaries, all become numbers in a spreadsheet eventually. Without good customer analytics, however, a business cannot really convert this information into knowledge...

Good Business Analyst Consultants - Here’s a comment. If anything I think good business analyst consultants or ones that have been outsourced, maybe they bring their experience and expertise to a client which would benefit the client going forward. I agree. I think you are right. I think they bring a different level of objectivity. I mean there is nothing quite like an outside pair of eyes. A practitioner of business analysis who is deployed in the client environment all the time, I think they are most appreciative of the fact that I am coming in with a fresh set of eyes, and I am looking at things with almost a certain sense of naïveté. I am looking at it with a fresh set of eyes. So to some extent there is a ton of value. I agree with you. Is the solution development lifecycle a new standard in the BA world? I don’t think so. This has been a terminology that has been around for a 100 plus years. Gosh, I have been in the business for 22 years, and I know people who have been in it longer. Solution development lifecycle has been around for a long, long, long time...

Good IT Analytics Tool - With a good IT analytics tool, you can drill down. You can do all sorts of things, but the important thing is, #1, looking at it from the business perspective, in terms of really how you are delivering that service, because that’s why you exist in a sense. And then, what’s the history of doing it, and how you are going to do that in the future, and then, it becomes a vehicle for conversation between the business and IT and the data warehousing people to understand where you are going and to understand your options. We can do it this way or that way, and here’s the cost involvement. We can look at all of those details, and we can figure out what’s the best way to move forward. Think about how this would impact the relationship between IT and businesses. Getting back to changes the culture between them because in the beginning, that’s “Oh, my God, this is broken, we will fix it as soon as we can.” This tends to be not a great relationship with the business side because the business side tends to look at IT, “The system is down, or it’s going down for a day.” Whereas when you arm them with this type of information, they become proactive, and now, they are having a business conversation with the other side of the company saying, “Look, here is what we are doing, here is how we are serving you, which is great, but here is what we need to plan for this.” That’s a completely different culture and conversation...

How the Analytics Software Facilitates the Discovery Process - Could you talk about how the analytics software facilitates the discovery process? You say using visual analysis software, you can facilitate that process, and I understand that, for example, you will connect a data set to an application that you purchase, and you bring in certain columns or certain fields of course and then basically can you run a preview then apply different algorithms and kind of get different visualizations? Do you look for the spikes in the trend lines, or the red areas or the green areas of a heat map? Flaherty: I think the way things used to be done with someone with tremendous experience and education in this area is he would start by doing all that work himself. I think as the visual analysis tools have gotten better, we can either bring in different types of people with less experience or make that expert much more productive. And one of the ways that we can do that is to not start off with a whole bunch of manual data transformations that could take the next two months putting together. Let the analytics software automate the data transformations. A lot of the visualization tools now have the capability to do some level of automated data transformations to get that started. So you know with the typical example would be there are always dates in a file. You can't use a date to predict anything, but you can use a time interval. So a lot of the software will automatically do that conversion...

How Important Is It to Your Organization to Have Analytics? - How important is it to your organization to have each of the following analytics and metrics related analyst capabilities. The choices were search for existing data, analytics and metrics. One of the reasons your projects might fail is if the data is not getting prepped and delivered quickly or properly. Two-thirds of the organizations surveyed spend more time prepping the data than actually analyzing it. If your customers have not tackled the data preparation process, it's going to reflect poorly on your BI solution because people are going to just say, I don’t have the information I need, because they are spending too much time in the data preparation process. Does that also include the activities of exporting data from databases and bringing into the spreadsheet because that’s where the person is going to analyze it? Waiting for data is one of them, believe it or not. Preparing the data for analysis, reviewing it for consistency and then the others are what they are actually doing once they are analyzing. But add up those pieces, waiting for data, preparing it, reviewing it for quality and consistency, that’s 69% of the organizations do most of their time...

How to Apply Predictive Analytics in Business - Today’s topic is How to Apply Predictive Analytics in Business. These economic times require changes in how businesses manage, in particular, the use of critical information to optimize decision making and other business processes. But getting this information is not simple. It can’t be found in historical reports but instead requires a forward looking analytics that can help gain insight on potential outcomes from existing operations. Then how do you build predictive analytics into your management efforts and what are the issues you need to be aware of this? This podcast is designed to provide prospective on you use predictive analytics actively and as an ingredient to your success. We’re talking today about analytics, but we’re talking in the context of an entire new environment of competitive and global business pressures. How do those two relate? Well the current economic environment is not a pretty one and second of all, the pace of business is increasing quite dramatically. So as we look at those two facts, one of the things that is pretty obvious is that if we’re going to make improvements in this type of economic environment we’re going to have to have information, and we’re going to have to make decisions on a very timely basis. Both of these realizations correlate together and make it a pretty complex environment for organizations...

Key Ingredient for a Successful Business Analyst - The second key ingredient for a successful business analyst is having good business skills. One of the things I hear an awful lot from the business analyst community out there is the challenge that they have to sit at the conference table with senior executive leaders and quantify strategies about the next fiscal year. Where are we going? What are we doing? What sort of insights do the senior BAs have? How can we guide the future? I think the profession still needs to grow, I think the acknowledgement still needs to be there, but I also think one of the missing pieces is what I would call ownership accountability. We need to get in synch with the phases our executive management team is using, return on investment and the creation of efficiencies. You should be able to talk about strategic plans and be able to articulate it. Be able to present that information which is relevant and important to a senior executive audience. I am not suggesting that we don’t do this already, but I’m suggesting that we need to really fine tune this ability. Things like critical thinking and problem solving, change management, things like integrity, things like setting goals and objectives, these are all the soft skills that are important...

Liberating Analysts and Managing Output - Now, obviously on the BI side what we try to do is to get ahead of these spreadmarts by encapsulating as many of them as possible into various data marts and data warehouses. And this is a never ending process and one that we need to take on and never get defeated in pursuing, but it is kind of like playing whack a-mole because it seems as soon as we consolidate one spreadmart into a data mart or data warehouse, two or three pop up to take its place. Nonetheless through a very persistent and consistent creation of new subject areas within a warehouse and proper application of BI governance, we can get ahead of the spreadmart dilemma that afflicts many of us. But, since we are talking about analytics and business analysts in particular, we have to ask why do these analysts create these spreadmarts? So I have got here the true deepest confessions of a real honest to goodness business analyst. And she’ll remain anonymous for the time being. She said, “I have been one of those so called “spreadsheet jockeys,” and I have an affinity for Excel, but out of necessity. Often the BI team generates a report that gives me 90 percent of what I need...

Making a Dashboard Solution Plug into Predictive Analytics - Now let’s talk in terms of making a dashboard solution plug into predictive analytics. There is something called PMML. That’s industry standard language, it’s called Predictive Modeling Markup. And PMML is a way that you can exchange predictive models to run against standard databases. So a BI solution should support PMML. Analytic solutions like SAS and SPSS can output PMML structures, and you just need to have a way to import them. There are a couple of issues there but delivery formats that are appropriate for organizations, so dashboards, alerts, mobile capabilities, time limits, we talked about. There are lots of problems with spreadsheets. One of the things we see that distinguishes the innovative firms is they are delivering information in a much more timely fashion. You can see a huge difference between the innovative firms and the tactical ones. Does timely mean day prior information...

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