Using Analytics for Sales: Internal Data Highlights External Sales Opportunities

December 15, 2009 –

Crafting a good sales pitch can be difficult. Getting the right data, hitting the right client pain points, crystallizing why your services are better than the competitors, all takes hard work. Honing your sales pitch to an art takes time, and even with a perfect picture, new clients take time to acquire. One of the best ways we’ve found to build a good sales pitch is to use data you already have.
In the digital world, there is no shortage of data, which translates into no shortage of potential competitive insights and advantages. With databases, data warehouses, corporate intranets, best practice sharing, web analytics, voice of the customer information, and QA or Six Sigma data, you are well-poised for discovering good information.

Finding ways to mash those together into meaningful new understanding is the key. Here’s an example of an analysis we performed for a client. They wanted to know how they could meet more of their current customers’ challenges. This would result in higher client satisfaction, increased revenue (from cross-sells), and could help them in future sales efforts with potential clients.

We took their entire list of current clients and added the following data:
• Industry
• Number of employees
• NAICS/SIC code
• Site locations with latitude/longitude coordinates
• Number of times they had been serviced (grouped by dates)
• Customer satisfaction survey data

This gave us a holistic view of challenges faced by specific industries. To obtain this, we used data from our client’s data warehouse as well as used LinkedIn, Yahoo Finance, Dun & Bradstreet databases, Client websites, and social media. Doing this definitely took work, but it highlighted thousands of dollars worth in future revenue and client retention. See a portion of the analysis below.


This graphic depicts problems our client's customers faced. The customers are grouped by industry.

 

For example, we quickly saw that the challenges faced by the banking industry were different than those faced by the inorganic chemicals industry. But we also saw that the challenges within industries were relatively the same. All the chemical companies struggled with the same things.

Using insights like these, we were able to pinpoint those clients who were lagging behind their industry peers in dealing with a certain challenge. This created cross-sell opportunities for our client. They were able to take the data and highlight these problems to their customers and show how their solution was solving similar problems for other members in the industry. This not only improved revenue, but also will increase customer satisfaction scores, as well as create more focused sales opportunities in the future.

Similar insights and opportunities are lurking in your own data. You just need someone to unlock them for you.

What do you think? Using the same data, what other ways could it be analyzed to find insights? How have you found insights in your own corporate data? Share your story.

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By Vault Analytics | Posted in Marketing Strategy, Sales Analytics | Tagged , , | Comments (0)

Twitter Efficiency Metric: Total Retweets /# of Followers

December 11, 2009 –

How is it Calculated?

For a given period of time, it’s simply your total retweets (given by Klout, see yesterday’s post) divided by your total number of followers.

Business Goal

This metric points to is how much you are thought of as a thought leader from your follower base. Becoming a thought leader has benefits for virtually any business because it has the effect of gaining the trust of your customers. As this number increases, it shows that you are increasing in thought leadership, as more and more of your followers are retweeting (you can think of it as syndicating) your thoughts, and recognize them as useful or authoritative.

How do you increase it?

Two ways – One, target your audience better. If the people following you are really interested in your business, then it’s easier for them to pay attention to what you say. Two, work at refining your message and the delivery of message. How you say something, and the medium you use, can have a big effect. Do your followers respond better to videos, podcasts, whitepapers, case studies, blog posts, or photos? Do some experimentation to find out what works best for your audience, and link to those things from Twitter.

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By Curtis Seare | Posted in Metrics, Twitter Analytics | Tagged , , | Comments (0)

Twitter Message Amplification Metric: Total # Retweets

December 10, 2009 –

How is it Calculated?

It’s just the total number of times that your tweets have been retweeted in a given time period. You can get this one from Klout as well.

total retweets

 

Business Goal
If it’s important for you to reach as many people as possible with your message, this is a good metric. It’s generally good for B2C firms, as the more people that know about your product the more customers you receive. The metric shows message amplification – as the number of retweets goes up, the amount of people that see your message increases dramatically. Since the average Twitter user has a few hundred followers, retweets have the potential of reaching a lot of people. It also shows how interesting or easily sharable your message is, indicated how likely it is to spread by other mediums besides Twitter. Measuring the retweets for specific tweets would also be useful to test and try which messages are the most sticky (for this you can use tweetmeme).

How do you increase it?
You increase this by sending out messages that are useful, valuable, interesting, and targeted to your followers. Another factor is your authority – if people recognize you as a leader in your industry, they are more likely to trust your tweets and retweet them. Retweeting other people’s material (participating in the community) will also help increase your retweets by the law or reciprocity.

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By Curtis Seare | Posted in Metrics, Twitter Analytics | Tagged , , , | Comments (1)

Twitter Engagement Metric: Follower Mention %

December 9, 2009 –

How is it Calculated?
The amount of followers that have mentioned you with an @ message / Your total number of followers. The easiest way to get this one is by signing up for a free Klout account, and it will automatically be calculated for you.

Twitter Engagement Metric

Twitter Engagement Metric

Business Goal

Follower mention is an excellent engagement metric. It indicates to what extent you are connecting with other users on twitter and developing real relationships. It can also be indicative of how valuable your tweets and content are to others, as the more value they see in what you have to say, the more likely they are to mention you.

If one of your business goals is to become a thought leader in a certain niche, or to build a larger community base of people that trust you and that you can do business with, then this is a good metric to follow. This is a valuable goal for almost any company, but especially for B2B firms, as sales in that situation requires good relationships and high levels of trust. To be sure if this metric is for you, you should probably ask yourself the following questions:

Is my target audience on Twitter? (try checking Twellow or Twitter search)
Are the people that influence my clients and customers on Twitter?
Is building a strong online community important for my businesses success?
Could I find potential partnerships or other opportunities from a Twitter community?
Is user engagement an important part of my brand and business?

How do you increase it?
You increase this metric by being social and helpful to others. An important part of this is reading other people’s tweets so you know who they are and what they are thinking about. Then you can start conversations with them, mention them, ask them questions, retweet them, give referrals to them, etc. Common courtesy also goes a long way; if someone else’s tweets are useful to you, let them know and thank them. And if you are mentioned in that way, be sure and let them know their mention of you is appreciated.

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By Curtis Seare | Posted in Engagement Metrics | Tagged , , , , , | Comments (0)

A Case for Analytical Marketing and Metrics

December 8, 2009 –

Some people try and debunk the move to analytical marketing. Their arguments are usually that the numbers don’t matter, that it’s impossible to track things such as social media, and that getting caught up in analysis takes you away from what’s really important in marketing. Many of these arguments come simply because the person arguing the point doesn’t understand how to do analytical marketing in a way that produces real insight and real results.
Light streaming through forest
Knowing how to design marketing campaigns that can be tracked and measured requires careful planning and skill. But considering the benefits of being able to know if the marketing money you’re spending is moving the needle, it’s well worth the effort. Data analysis and campaign tracking has the added benefit of allowing you to see otherwise hidden insights so you can make changes to your marketing strategy and gain optimal results. If you are foregoing the use of metrics and analytics, you are stuck in the trees without a view of the forest.

According to your specific business and goals, there are various metrics you can use to help you track your progress and optimize your strategy. Once you know your goals, you can think through which metrics will help you reach them. To this end, the next several posts will be dedicated to goal-based metrics. We will examine specific metrics, what they tell us, how they are calculated, the best ways to implement their tracking, and what business goal they help us achieve. The hope is that you will be able to take some of these metrics and implement them to enhance your own business strategy.

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By Curtis Seare | Posted in Marketing Analytics | Tagged , | Comments (0)

Using The “Linest” Function in Excel For Faster Twitter Potential Reach Analysis

December 7, 2009 –

Last time we looked at a way to put together an analysis for the potential reach of a tweet; today we’ll look at a method of using the ‘linest’ function in excel to make the analysis faster. When you go to Twellow to look up the users that would be interested in your business, it will give you a long list of profiles. The only way to get the data into Excel is to type it in manually, so if we want the entire list of sometimes thousands of users, we need a way to cut back on the amount of time it takes. Here’s the method in a few steps:

1. List manually the first 10 to 20 names; you want to be exact with the users that have a substantial amount of followers.

2. After the really large users are entered in, you’ll notice that the number of users doesn’t change drastically from, say, user 25 to user 40. So, we’ll just enter in the two users and use a regression to fill in the rest. This makes our work faster, and we’re still close enough on the numbers for our analysis. How to do this is shown below.

Set up for the regression

Set up for the regression

 

Setting up the linest function

Setting up the linest function

Remember to important things when setting up the ‘linest’ function:
1. Make sure an highlight two adjacent cells before typing it in.
2. After entering the formula, hit ctrl+shift+enter

 

Filling in the data

Filling in the data

Repeat this as many times as necessary to get the complete data set. As you keep going, you can increase the intervals from 15 to 50 to 100, etc.

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By Curtis Seare | Posted in Excel | Tagged , | Comments (0)

Potential Reach of a Tweet

December 5, 2009 –

How do you show the online marketing opportunity for a new business venture? One piece of the online space that you will want to show is Twitter. Here’s an attempt at gauging how much reach your tweets would have.

To start the analysis, head over to Twellow and search for users that would be interested in the new business. Twellow gives you a long list of people that could be interested, and from that list we can start creating a spreadsheet with the user name and the number of followers they have.

The rest of this analysis assumes we get each user to tweet once about our new business. The question is, how many people will be aware of us as a result? The completed sheet below answers that question.

Tweet Reach

 

The % Views is our best estimate of how many of the user’s followers will actually read the tweet.

The Awareness is the number of followers the user has multiplied by the % views, giving us how many people actually read the tweet.

Then we get into the retweets. The % that Retweet is the percentage of aware people that we think will be interested enough to retweet.

The # of retweets is the % that retweet multiplied by the awareness

The average # of followers is the average of each of the users followers on the list, to give us the number of followers the average user has.

Multiply the number of retweets and the average # of followers, and you get the potential number of people that can be reached from the retweeting, or Potential Reach.

Multiply this by the % views, and you get the Awareness reached by the retweeting.

Finally, add up both awareness columns to get the Total Awareness. This number is an estimate of the number of people that will be aware of your business as a result of that user tweeting about it once.

Obviously there are many assumptions made here, but it gives you a good idea at just how powerful a tweet could be to increase awareness of your product or service.

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By Curtis Seare | Posted in Twitter Analytics | Tagged | Comments (0)

Confused People Don’t Act

December 4, 2009 –

Let’s illustrate further the principles discussed in yesterday’s post. Sometimes it’s best to learn by example, so I’ve embedded two ads below. Take a look.

 

Although both of these commercials can be considered entertaining, one of them was effective and the other a failure. It’s easy to see why when you consider which one of them makes it easier for the viewer to incorporate the message into their lives.

In the first ad the viewer hears the name ‘Outpost.com’, and then see a pack of wolves attack a high school band. What is the viewer supposed to do with that? Apparently they weren’t sure, because Outpost.com is no longer in business.

The second ad gives the viewer a natural scenario (making a sandwich with peanut butter, and wanting milk with it) and then ends with the interrogative: got milk? Well, if the viewer doesn’t have milk, he or she needs to go get some. Easy and simple. And incidentally, the ‘Got Milk’ advertising campaign was one of the most successful in history.

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By Curtis Seare | Posted in Content Creation | Tagged , | Comments (0)

Build Content That Helps People Act

December 3, 2009 –

We market to people because we hope that our messages will spur them to take action. Can your audience easily see how your message fits into their lives? If not, there’s a good chance they won’t take any action on it.

In Malcolm Gladwells’ book, The Tipping Point(affiliate link), he cites an interesting case study. An experiment took place at Yale University trying to convince students to get a tetanus shot; two different packets of information were prepared with information about the benefits of getting the shot. One was purely informational, and one was aimed at instilling fear in the students by describing potential consequences if they didn’t get the shot. After the students were split up and each group was allowed to read one of the packets, they took a survey which would indicate which group was more motivated to get the shot. Predictably, it was the ones that received the packet aimed at instilling fear.

Only a very small percentage of students, however, went to get the shot. And totally unexpectedly, there was no difference in between the two different groups. The fact that one of the packets instilled fear, and that the students who read it seemed more motivated to get the shot, made no difference in their actual behavior.

The experiment was done again, and this time there was a small change made – in the packet was included a map of the university campus with the health center giving the shots circled, and a list of the times the center was open. This one small change resulted in a 28% increase in students getting tetanus shots.

Why did the percentage raise so dramatically? Because the map made the message fit into the students lives. It took the information from an abstraction to something practical and actionable. And that made all the difference.

Help your audience see how to apply your message. If they can picture themselves taking action, there are higher chances that they actually will.

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By Curtis Seare | Posted in Content Creation | Tagged | Comments (1)

Web Analytics and Online Revenue

December 2, 2009 –

A little while back we did some work with a company’s web analytics data. Their online revenue had doubled, and they wanted to know why. The answer to the question was not obvious, and only after extensive analysis did it present itself. It’s useful to see the process of how to use web analytics to come to a conclusion. The analysis was written up on the Tableau Software blog; you can read the entire story here.

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By Curtis Seare | Posted in Google Analytics | Tagged , | Comments (0)