Five Important Things for All PPC Agencies to Focus On

Pay Per Click

There are certain things that every PPC agency should make a point of focusing on in order to become as successful as possible. It’s easy to lose sight of what’s really important when you are running a business, which is why it’s so important that you keep certain things in mind at all times.

When you learn which things you should concentrate on the most when running a PPC advertising agency, you will be able to serve your clients well. And the happier your clients are, the more likely they will be to keep paying for your services.

1.     Maintaining a Personal Connection with Clients

It is crucial that you put a lot of emphasis on creating and maintaining a personal relationship with each of your clients as well as potential clients. When they feel like you actually care about helping them reach their business goals, you won’t have any issues keeping them. There are so many faceless PPC agencies out there, and part of what so many people want is that personal touch.

2.     Innovative Solutions

It’s also imperative that you come up with innovative solutions for your clients. You aren’t going to last very long in this line of work if you are just doing the same exact thing as every other agency. You’ll need to get creative when it comes to helping your clients meet all of their goals, where businesses can rely on your PPC agency as a true partner. This is one of the biggest things to focus on when running this type of business.

3.     Solve Your Client’s Primary Issues

If you want to run a successful PPC advertising firm, you will need to solve each client’s primary issues, whatever they are. Whether your client is having issues with breaking into social media, or they are trying to figure out how to refresh their brand, it’s up to you to come up with solutions. You should ask each of your clients to describe the problem they are having in a succinct manner so you’ll have an easier time helping them with what they need.

4.     Make Your Website Professional and Attractive

Nobody will want to pay for the advertising services you have to offer unless you have a good-looking website that also appears professional. Make sure that you invest a decent amount of time into designing a website that is easy to navigate and is aesthetically pleasing.

5.     Communication is Key

People want an advertising agency that is good at communicating back and forth with them, so that’s exactly what you’ll need to provide your clients with. Make sure that you promptly respond to all queries so that none of your clients feel the slightest big neglected.

With all of the different PPC advertising companies that exist, you will need to make sure that you stand apart from the competition. As long as you put in the necessary time and effort, you should have no problems whatsoever maintaining a healthy number of clients. Pay-Per-Click advertising has become very popular over the years, so there is plenty of untapped potential out there to explore.

7 Reasons Why You Need Predictive Analytics Today

by Kaitlin Noe –


How did you learn to keep your hands away from hot stoves? If you burned yourself on a stovetop when you were younger, then you now use the knowledge gained from that experience to predict what will happen if you accidentally touch a burner: You know to stay away. On a more complex level, predictive analytics does the same thing for your business. It uses your data to make connections based on past experience, and it applies that information to make predictions about what will affect your company in the future. The effects of employing predictive analytics can be astounding—so much so that some people are calling predictive analytics a necessary capability for keeping a competitive edge. The following are seven reasons why your business needs predictive analytics today.
1. Secure a competitive stronghold
Predictive analytics help you play to your company’s strengths and your competitors’ weaknesses. By tapping into the data surrounding your company’s experience, you generate insights unique to how you perform. Such insights are not outside common knowledge; rather, they provide a deeper awareness of how you are successful and where your organization’s individual advantage lies.

Alternatively, predictive analytics allows you to evaluate the actions of consumers who have been exposed to not only your but also your competitors’ marketing and sales. The modeling process learns to distinguish between customers who choose you versus those who select a competitor, identifying what factors played into their decision. It helps you play to your own strengths, pinpointing the areas where your competitors are failing.

Read more here:



Cloud Data Analytics Will Be the Key to the Future

By Shawn Drew –

When the cloud and big data surged onto the scene a few years ago, they seemed like they would be a perfect fit together. Now, new research from Forrester, reported by Information Management, has found that not only are they perfect together, but also that not utilizing advanced analytics can be detrimental to a cloud solution. Managed service provides (MSPs) have to learn how to combine the two to create a single cloud data analytics solution that fits all of their customers’ needs.

The Cloud and Big Data Need Each Other

According to Forrester’s survey of 275 IT decision makers and senior business executives, all reported at least one negative operational or financial impact with the cloud due to missing or hidden metadata — the kind that advanced analytics should be able to find. These negative impacts include outages, reporting failures, unnecessary costs and wasted resources.

The survey pins these issues on the fact that many cloud solution providers are not utilizing analytics to monitor the solution. Overall, this has led to low customer satisfaction with the cloud, with a general feeling that cloud solution providers are not invested in their clients’ success.

MSPs Can Lead the Trend

Forrester’s research also provides some insight into how MSPs should treat these two technology mainstays going forward.

By providing insight into how the cloud and big data work, MSPs can alleviate some client concerns and help them improve performance. Customers will naturally be invested in achieving better performance, so by simply providing analysis tools for these solutions, MSPs may find ways to better run clients’ entire operations.

By combining big data and the cloud, and by allowing them to power each other, MSPs will have a ready-made answer for prospective clients that solve the exact pain points they were experiencing.

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Bad Data Need Not Apply

By Paula Wiles Sigmon –

“Giving business and technical users data they trust is key to good business intelligence,” according to Philip Russom of The Data Warehousing Institute (TDWI). A new e-book from TDWI, Why Enterprises Need Trustworthy Data, explores issues like why we need trusted data, how to get it and what issues arise when we try to run a business based on data that doesn’t deserve our confidence.

We should be rolling out the welcome mat to invite good data into our data warehouses, and at the same time making it clear that bad data need not apply.

We’ve all seen the scenario where businesspeople simply don’t trust the reports they receive. In that scenario, what can the users do? They can base their decisions on the questionable reports anyway, ignore the reports and make decisions that are not based on fact or try to create their own systems to deliver data they can trust, creating more data silos and perhaps more of those “shadow IT” systems that keep cropping up around the enterprise. The options aren’t pretty.
The many data warehousing challenges
In an environment where lack of trust is common, the data warehouse challenge is not just finding the best warehouse technology or the critical data that lives in silos around the organization and determining what should move to the warehouse, although those are certainly important. It isn’t even just determining how to start leveraging unstructured information as part of the analytics environment, although that is a challenge that organizations face today as they tap into the new opportunities presented by big data. 

A key challenge in the current environment is determining how to create a warehouse that instills confidence among the business users who receive the output of analysis based on the warehouse. So what does it take to build that confidence? Is it consistent data quality? Yes, that’s part of the answer.  How about transparency into the lineage of the data: where it originated, who or what has changed it, and when it was last updated? Yes, absolutely. No one should have confidence in information from an unknown or unreliable source, or information that is woefully out of date.

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Medical Care Preparing for Cognitive Computing

Just the ability to access the data that individuals or doctors basically require might be largest breakthrough in the history of medical care.

Even during present days we are being unable to find the appropriate information both regarding way of living or therapeutic conclusions. Will it be the proper diet or workout routine for me? Is that the single research I have to review about a patient’s situation? This might transform with cognitive computing.

What precisely the most recognized professors understand cannot meet cognitive computers. Since the volume of data they collect increases tremendously, help of computing technologies in medical conclusions is setting out to go.

When a doctor could keep a small number of research outcomes and documents in memory, there exist countless files and from which to get prospective perception. At this point take into account IBM’s Watson could operate 500 GBs of data equal of million books in a moment. This outstanding performance has resulted Watson being utilized in oncology medical centers to start to assist medical professionals with treatment plans and conclusions.

Watson is available not to replace doctors, but to help them making judgements. Moreover it interacts with medical professionals and can recommend with extra medical tests are important to produce a better level of confidence.

Watson collaboration with clinicians shows ways it can likely enhance healthcare.

However in healthcare everyone should be ready to obtain cognitive computing’s capability. Physicians must start getting essential understanding of the way AI operates in medical environments in an effort to figure out how such products can help in daily jobs.

Just like stethoscopes those cognitive computers are going to be real methods in the medicine approach, but only if caregivers discover ways to utilize and benefit from technological innovation. Consider that many useful fragments of data relating a disease are instantly reachable whenever a patient is accepted to clinic. The doctor can quickly suggest possible individual ways for best result.

You need to be ready to take benefit from these innovative, cognitive computing solutions for quicker, trustworthy diagnoses and remedies.

User Request Web Content Prognostication

Discover ways to examine web server log files to learn ways of users website browsing and forecast next browsed content. This article explains applying extensible Markov model to cluster web pages on a website and predict the place user will move next. The algorithm utilizes InfoSphere® Streams and R for regular issue prognostications based on model.


Webserver log files are used to examine users surfing behaviour. As an illustration, in “Predicting Web Users’ Next Access Based on Log Data”, Rituparna Sen and Mark Hansen have utilized combination of first-order Markov models to examine clusters of pages on a website. They applied these models for prognostication which webpage user supposed to visit next. They suggested implementing this information to pre-fetch a resource before a real request by user. This article will explain how to use IBM InfoSphere Streams, combined with R to run an identical analysis of webserver logs.
This solution is implementing extensible Markov models (EMMs), initially released in 2004 by Margaret Dunham, Yu Meng, and Jie Huang, to mix a stream clustering algorithm with a Markov chain. A Markov chain is a mathematical system that reviews transformations from one state to other, in which the following state is relying only on present and not the sequence of proceedings that came before.
The states of Markov chain are aggregation specified by stream clustering algorithm. The EMM can transform eventually by including new states since they are discovered and also damping or trimming current states with time. Consequently, the model is able to make adjustments eventually. This opportunity is particularly crucial in systems with dynamic usage style that changes over the time. As an example, website will probably display dynamic usage pattern, as well as improvements in structure, in some time.

Advantages of integration

The majority of machine learning models designed for forecasting are performed offline on big amounts of training info. Right after the model are properly trained, prediction could be done right away. This technique is suitable for numerous sorts of issues, however if the patterns for prediction are changing regularly, this method could create models that drop behind the system they are attempting to forecast. Since EMM could be educated dynamically, they are effective for modelling systems like network traffic, auto traffic, or another system in which clustering patterns can transform eventually. Web server traffic is one of those sphere. Server logs deliver an infinite source of streaming information to educate the model when the system is already performing forecasting.

Prognosticating content requests from web server logs

Internet servers are keeping logs of resource queries. Every log entry consists IP address of user, timestamp for request, and the destination for requested data. All this information characterize user and requests to website.


This article shows how to forecast users actions on a website to predict content requests using webserver log files. The modelling and prognosticating are completed by applying EMM. The solution represented here is a testament to concept. Upcoming work is essential for developing a genuine solution. Next actions involve enhancing overall performance by clustering sets of webpages, incremental studying, and using InfoSphere Streams to carry several cases of R.

Cognos 10.1 install on CentOS 6.3 64 bit

  1. yum update (then reboot if kernel has been patched)
  2. yum install glibc.i686
  3. yum install openmotif
  4. yum install libgcc.i686
  5. yum install openmotif22
  6. yum install openmotif22.i686
  7. yum install xauth
  8. yum install libXtst
  9. tar xvzf bisrvr_linuxi8664h_10.1.1_ml.tar.gz
  10. cd linuxi38664h/
  11. ./isetup

How to Flatten a Dimensional Data Model Built in Excel with Pivot Tables

To flatten a dimensional model built in Excel using pivot tables, follow these steps:

  1. save the original worksheet with the pivot table as a CSV (tab delimited is even better)
  2. select the range or column that contains the blanks (if you have blanks under the header, don’t select the column header in the range)
  3. select Edit -> Go to… -> Special
  4. select blanks (at this point Excel will select all the blank cells
  5. press equal
  6. point to the cell above the first selected cell
  7. press <ctrl>+Enter and Excel will copy the formula to all the blank cells
  8. to replace the formula by the values, simply save the worksheet again as CVS, or copy and paste special the cells as values
  9. that’s it, you’re done. (Don’t forget to save.)

Intro to Statistics

Q: Could you recommend some books on statistics that would allow me to be more efficient at Business Analytics?


A: Below are some sites that you may find useful.

1)      The online copy of StatSoft, the Statistica textbook, a good resource, and it’s organized as a book.

2) UCLA has an online probability and statistics book, although it may be too elementary for you.

3)      Planet Math has a lot of very useful links.   If you scroll down the page for the URL below, you’ll see a link labeled 62-XX, Statistics.  (There are plenty of other valuable links too.)

4)      The Kahn has some excellent short videos on specific topics in statistics.  More generally, the entire site is very well regarded.

It you share the name(s) of the (text)book(s) that you’ve read I can identify which resources may be of the most use to you.  As I’m sure you’ve discovered, statistics fractures into a myriad of sub topics just like mathematics.  So narrowing this down will let me help you better.

Enterprise Social Media Analytics with Atlas for Connections

The key benefits from deploying an enterprise social media software are to improve

  • customer satisfaction by building stronger relationships with customers,
  • staff effectiveness by simplifying access to existing internal expertise,
  • staff retention by allowing employees to build a stronger network and stronger relationships within the enterprise.

Atlas for IBM Lotus Connections is a social networking application, available from IBM Software Services for Lotus (ISSL), that allows users to visualize their current network of contacts and see how they can efficiently extend that network to tap into valuable resources and trusted experts across an entire organization.

Atlas enables these capabilities by accessing information from the different components of Lotus Connections. When users log in to their dashboard, Atlas compiles and displays information that will help them better understand the company’s professional networks and who they can tap into these networks to increase their effectiveness day in and day out.

With the help of these different components, Atlas allows users to:

  • visualize and analyze social networks in an organization,
  • identify the shortest path to reach someone,
  • find expertise across extended networks,
  • visualize and manage their personal networks.

Contact us to leverage this social networking and visualization application to help your company build vibrant and balanced professional networks, increase team effectiveness, and improve individual productivity.

Watch this brief demo from IBM demonstrating how to unlock the value of enterprise social media.