While this blog usually focuses on theory and modeling customer satisfaction and loyalty, it will, from time-to-time, discuss topics that are a little outside the normal discourse. Such is the case today where brief discussion of customer capital has some relevance to the topic of satisfaction and loyalty. This blog is the result of re-reading a book published in 1997 titled "Intellectual Capital" and was written by Thomas A. Stewart. Reviewing some of his concepts about how companies and customers can interact gave me some ideas that relate customer capital to loyalty. The idea is that both the company and its customers have knowledge that may yield greater benefit and loyalty when combined.
Successful companies will invest in employees because they know that employees are knowledge sources for the company. As employees become better trained and knowledgeable, they also become more likely to create knowledge assets, usually referred to intellectual property.
But when we examine the company from a broader perspective the question becomes can the company also form a relationship with its customers that might create knowledge assets? The obvious answer is yes. The combined resources of the company and its customers can very likely create knowledge that may provide new asset value to both. This seems to be an opportunity that many companies are missing.
It is clear that when a company solves a customer problem there may be some new knowledge created from the solution. However, these circumstances where new knowledge is created are more spontaneous that planned and rarely make it into any category of either the company or its customer that would identify the new knowledge as capital. Some of the more dramatic company-customer solutions may lead to a shared patent or copyright as well as a stronger relation with the customer. Another benefit of these new knowledge solutions might be another way to differentiate a product or service from the competition and lead to increased margins.
The bottom line is the company-customer interface is rarely seen as a place to create new knowledge capital even though the benefits are obvious and may actually lead to significant product and service breakthroughs. The challenge is to change the way we look at customers. Customers are no longer simply a source of revenue. They also bring the opportunity to create knowledge capital jointly with the company that can lead to a stronger customer relationship with the company as well as create barriers to competition that are built from the new knowledge.
Saturday, May 15, 2010
Wednesday, May 12, 2010
The Other Side of the Coin
In the previous blog, it was noted that when high performance agents became at-home agents, their performance deteriorated. Customer satisfaction decreased. There appears to be another side to this situation. The inContact consulting firm has written a white paper titled "The Work-at-Home Agent model for Improved Customer Loyalty". Some of the statistics presented include:
1. A national poll conducted by inContact in 20007 showed that 46% of respondents (presumably businesses with call centers) said they were using at-home agents.
2. A study published by The Telework Coalition noted that the at-home contribution on improving the bottom line included 91% of agents were happier, had increased productivity, a higher retention rate, and reduced office space and operational expenses.
3. Frost & Sullivan report the median age of an at-home worker is 38 while the average age of an on-premises call center agent is 23 and further noted that 80% of at-home agents have some college-level education compared to 35% of agents in the on-premises centers.
4. According to a Gartner Group survey, at-home agents measured 40% more productive.
5. IDC Consulting has published results that indicate an on-premises agent costs $31 per our while an at-home agent costs $21 per hour on average.
6. The Interantional Telework Association and Council have published statistics the show there is a space savings that can reach $12,000 per employee per year. They also appear to indicate that there is a decreased cost of $25,000 per at-home employee compared to a traditional call-center agent.
These are strong statistics which suggest there may be an impact on customer satisfaction and loyalty. However, please note there were no statistics that compared customer satisfaction between at-home agents and on-premises agents.
The bottom line is that while these statistics are encouraging, there is no measured difference between the in-home agent and the on-premises agent for customer satisfaction. The Customer Institute will continue to search for studies that attempt to measure the satisfaction impact of the at-home agent. While this white paper has good content and meaningful statistics, it can only suggest that at-home agents may improve customer loyalty.
1. A national poll conducted by inContact in 20007 showed that 46% of respondents (presumably businesses with call centers) said they were using at-home agents.
2. A study published by The Telework Coalition noted that the at-home contribution on improving the bottom line included 91% of agents were happier, had increased productivity, a higher retention rate, and reduced office space and operational expenses.
3. Frost & Sullivan report the median age of an at-home worker is 38 while the average age of an on-premises call center agent is 23 and further noted that 80% of at-home agents have some college-level education compared to 35% of agents in the on-premises centers.
4. According to a Gartner Group survey, at-home agents measured 40% more productive.
5. IDC Consulting has published results that indicate an on-premises agent costs $31 per our while an at-home agent costs $21 per hour on average.
6. The Interantional Telework Association and Council have published statistics the show there is a space savings that can reach $12,000 per employee per year. They also appear to indicate that there is a decreased cost of $25,000 per at-home employee compared to a traditional call-center agent.
These are strong statistics which suggest there may be an impact on customer satisfaction and loyalty. However, please note there were no statistics that compared customer satisfaction between at-home agents and on-premises agents.
The bottom line is that while these statistics are encouraging, there is no measured difference between the in-home agent and the on-premises agent for customer satisfaction. The Customer Institute will continue to search for studies that attempt to measure the satisfaction impact of the at-home agent. While this white paper has good content and meaningful statistics, it can only suggest that at-home agents may improve customer loyalty.
Saturday, May 8, 2010
Some Surprising Findings
Call centers represent one of the fastest growing segments of customer service. A recent blog by Carmit DiAndrea of Analytics & Client Services brought this to the attention of The Customer Institute. There has been a trend toward work-at-home agents and some of the data suggest the number of work-at-home agents is growing at the rate of 40% per year. Other studies indicate the attrition rate of work-at-home agents is much less than the typical call center. One of the prime reasons is that work-at-home agents eliminate the cost of work space. While this may be of interest to those who watch the financial aspect of call center operations, the point of this blog is that in one case study there were two surprises. These surprises lead to the question: "is this an anomaly or is there something to this that needs to be investigated."
The first surprise was the likelihood to recommend the company's services was somewhat lower for the work-at-home agent than the call center and the second surprise was that satisfaction with service provided was also lower for the work-at-home agent than the agent at the call center.
Let me enter a few caveats here; namely,
1. This is only one company that recorded these results and that company has chosen to remain anonymous.
2. The differences between the call center agents and the work-at-home agents were concluded to be different but there was no test to determine if the differences were statistically significant.
3. This was not a controlled experiment. Thus, there may be other factors that caused the differences.
The company tracked these two parameters metrics for one year and based on the data asked the following questions:
1. Why did these metrics drop when one call center sent their top performing agents home to work?
2. What would cause these top agents to struggle to perform at an average level?
While there were no clear answers to these questions, the following ideas were presented without any evidence that they may be significant:
1. How were the work-at-home agents selected? Is there a difference between agents in the call center and work-at-home agents? Does it take a different type of person?
2. Should the expectations be different for the call center agent than the work-at-home agent?
3. Can the type of training make a difference?
4. Should the management of call center agents be different than work-at-home agents?
The bottom line is that there appears to be a sea change in the work force for call centers. Some of the questions that need to be addressed are:
1. Do we need a new way to train managers to manage the work-at-home agent?
2. Do we need to train work-at-home agents differently than the call center agents?
3. Do we need new metrics for the work-at-home agent?
4. Should there be different hiring requirements for call center agents than work-at-home agents?
Since we know that call center agents have a direct impact on both customer satisfaction and loyalty, this topic needs more research. One case is not enough. We are interested in the outcome and will blog any further results that are published.
The first surprise was the likelihood to recommend the company's services was somewhat lower for the work-at-home agent than the call center and the second surprise was that satisfaction with service provided was also lower for the work-at-home agent than the agent at the call center.
Let me enter a few caveats here; namely,
1. This is only one company that recorded these results and that company has chosen to remain anonymous.
2. The differences between the call center agents and the work-at-home agents were concluded to be different but there was no test to determine if the differences were statistically significant.
3. This was not a controlled experiment. Thus, there may be other factors that caused the differences.
The company tracked these two parameters metrics for one year and based on the data asked the following questions:
1. Why did these metrics drop when one call center sent their top performing agents home to work?
2. What would cause these top agents to struggle to perform at an average level?
While there were no clear answers to these questions, the following ideas were presented without any evidence that they may be significant:
1. How were the work-at-home agents selected? Is there a difference between agents in the call center and work-at-home agents? Does it take a different type of person?
2. Should the expectations be different for the call center agent than the work-at-home agent?
3. Can the type of training make a difference?
4. Should the management of call center agents be different than work-at-home agents?
The bottom line is that there appears to be a sea change in the work force for call centers. Some of the questions that need to be addressed are:
1. Do we need a new way to train managers to manage the work-at-home agent?
2. Do we need to train work-at-home agents differently than the call center agents?
3. Do we need new metrics for the work-at-home agent?
4. Should there be different hiring requirements for call center agents than work-at-home agents?
Since we know that call center agents have a direct impact on both customer satisfaction and loyalty, this topic needs more research. One case is not enough. We are interested in the outcome and will blog any further results that are published.
Saturday, May 1, 2010
Butterfly Customers
I recently found a book published in 1997 titled "The Butterfly Customer - capturing the Loyalty of Today's Elusive Customer." The authors Joan A Pajunen and Susan O'Dell describe what now appears to be a very different customer. They describe butterfly customers as customers who flit from one store or supplier to another with the intent of finding a lower price or some other feature. They have no loyalty to any particular company and are always in search of a better deal or a new inducement.
The reason I am attracted to this concept is that I believe I am a butterfly customer. According to the authors butterflies have developed from the proliferation of shopping environments such as shopping malls and the Internet. The small company or retail store might offer convenience but cannot match the pricing of large companies. (When I worked in industry I worked for a division of a company that held 3rd place in market share. The two companies that fought out the 1st and 2nd place could sell products for less than our manufacturing cost).
The authors provide eight characteristics of butterflies.
1. They will readily accept offers to be loyal customers.
2. They move across market segments. They will buy a luxury item and then go to a discount store to save a few dollars.
3. They are intelligent, educated and informed.
4. They are cynical and skeptical, and always read the fine print.
5. They would rather switch than fight - which may be a reason for the decline in customer complaints.
6. They consider word-of-mouth as the most reliable source of information.
7. They are not embarrassed to be butterflies.
8. They know their own worth.
The authors describe a butterfly that can be loyal. The "Monarch" is a butterfly who will return again and again once he/she trusts the company. There are five characteristics of Monarchs.
1. Monarchs always return sooner or later.
2. Monarchs often send someone in their place.
3. Monarchs always have an opinion which they will share if asked.
4. Monarchs share their homework and may share their information on what the competition is doing.
5. Monarchs are very forgiving and giving. They have elasticity in their transactions which translates that they will overlook a mistake or bad transaction.
The solution offered for building an environment to create Monarch butterflies has three dimensions; namely media, physical (bricks and mortar) and people. When these three dimensions are working together the customer can develop trust in the company. If any of these dimensions are out of sync, the trust may not develop. For example, a company that provides a media image of high quality and provides a quality product but has surly personnel will create dissonance in the mind of the customer. Loyal Monarchs can be found dealing with companies that provide consistency in these three dimensions.
The bottom line is that customers may, in fact, be changing as a result of the media. The concept of butterflies resonates with me. The concept of butterfly customers has not taken off in terms of the literature. It is always surprising how many creative ways are being developed to describe customers and segment the market and butterflies may be a new segment. It will be interesting to see whether or not butterfly customers do become a segment. In any case, the butterfly customer just may require a new definition of loyalty.
The reason I am attracted to this concept is that I believe I am a butterfly customer. According to the authors butterflies have developed from the proliferation of shopping environments such as shopping malls and the Internet. The small company or retail store might offer convenience but cannot match the pricing of large companies. (When I worked in industry I worked for a division of a company that held 3rd place in market share. The two companies that fought out the 1st and 2nd place could sell products for less than our manufacturing cost).
The authors provide eight characteristics of butterflies.
1. They will readily accept offers to be loyal customers.
2. They move across market segments. They will buy a luxury item and then go to a discount store to save a few dollars.
3. They are intelligent, educated and informed.
4. They are cynical and skeptical, and always read the fine print.
5. They would rather switch than fight - which may be a reason for the decline in customer complaints.
6. They consider word-of-mouth as the most reliable source of information.
7. They are not embarrassed to be butterflies.
8. They know their own worth.
The authors describe a butterfly that can be loyal. The "Monarch" is a butterfly who will return again and again once he/she trusts the company. There are five characteristics of Monarchs.
1. Monarchs always return sooner or later.
2. Monarchs often send someone in their place.
3. Monarchs always have an opinion which they will share if asked.
4. Monarchs share their homework and may share their information on what the competition is doing.
5. Monarchs are very forgiving and giving. They have elasticity in their transactions which translates that they will overlook a mistake or bad transaction.
The solution offered for building an environment to create Monarch butterflies has three dimensions; namely media, physical (bricks and mortar) and people. When these three dimensions are working together the customer can develop trust in the company. If any of these dimensions are out of sync, the trust may not develop. For example, a company that provides a media image of high quality and provides a quality product but has surly personnel will create dissonance in the mind of the customer. Loyal Monarchs can be found dealing with companies that provide consistency in these three dimensions.
The bottom line is that customers may, in fact, be changing as a result of the media. The concept of butterflies resonates with me. The concept of butterfly customers has not taken off in terms of the literature. It is always surprising how many creative ways are being developed to describe customers and segment the market and butterflies may be a new segment. It will be interesting to see whether or not butterfly customers do become a segment. In any case, the butterfly customer just may require a new definition of loyalty.
Tuesday, April 27, 2010
More Thoughts on Disloyalty
Maritz Marketing Research published a research report titled "Customer Disloyalty". The report was written by Dr. Dan Lockhart. He starts out by saying that loyal customers have the following characteristics:
1. Like your product and/or service
2. Frequently purchase your product and/or service
3. Feel your product and/or service is worth what they paid for it
4. Feel that your product and/or service is better than your competitors'
5. Feel you product and/or service meets their expectations or desires
6. Recommend that others purchase your product and/or service.
He then defines disloyal customers as "anti-customers for the following reasons:
1. They dissuade others from patronizing our business
2. They bring law suits against you
3. They may complain about you to the media
4. In extreme cases they may picket your business.
According to Dr. Lockhart there are 4 stages of disloyalty:
Stage 1 - the customer is dissatisfied or has unmet expectations or desires.
Stage 2 - there is an attempt to correct the situation if the company is aware of the dissatisfaction or unmet expectation.
Stage 3 - If the company fails to correct the problem the customer may refuse to make any additional purchases
Stage 4 - If the customer feels he/she has no other option that customer may attempt to influence others not to buy from the company.
These four stages represent the downward spiral that begins with a dissatisfied customer and ends with a lost customer.
The research report uses a tree to show where customers get lost through the various stages of disloyalty. The tree starts with 1200 customers. The first stage (two branches) shows that 960 customers (80%) have no problem and 240 have a problem. Of the 240, (the second stage with two branches) there are 48 customers with a problem (this represents 20% of those with a problem who don't tell anyone and start down the path to disloyalty). Of the 192 that do tell someone (the third stage with two branches) 86 get excellent results (45%) and 102 do not get excellent results and start on the path to disloyalty. Finally in the fourth stage there are two branches that show half of those who received excellent response decide to purchase again and the other half chose not to repurchase. When all of these probabilities are combined there are 197 customers out of the original 1200 (16.4%) who end up on the road to disloyalty.
One of the obvious conclusions that can be drawn from this discussion is when companies do not handle complaints very well they are accelerating the decline from dissatisfaction to disloyalty. The data used in the research paper to create the probabilities was from a client and hence has some validity. While these probabilities represent the performance of just one company, the conclusion drawn by Dr. lockhart makes sense.
The bottom line is that managing customer complaints well appears to have a dramatic positive effect on customers with the implication that the company also benefits in terms of reducing the number of customers that may become disloyal. The challenge for companies is to examine the magnitude of these four stages that lead to disloyalty. One way to think about these four stages is to see them as cracks in the organizational structure. Then it becomes a management problem of how best to fill the cracks.
1. Like your product and/or service
2. Frequently purchase your product and/or service
3. Feel your product and/or service is worth what they paid for it
4. Feel that your product and/or service is better than your competitors'
5. Feel you product and/or service meets their expectations or desires
6. Recommend that others purchase your product and/or service.
He then defines disloyal customers as "anti-customers for the following reasons:
1. They dissuade others from patronizing our business
2. They bring law suits against you
3. They may complain about you to the media
4. In extreme cases they may picket your business.
According to Dr. Lockhart there are 4 stages of disloyalty:
Stage 1 - the customer is dissatisfied or has unmet expectations or desires.
Stage 2 - there is an attempt to correct the situation if the company is aware of the dissatisfaction or unmet expectation.
Stage 3 - If the company fails to correct the problem the customer may refuse to make any additional purchases
Stage 4 - If the customer feels he/she has no other option that customer may attempt to influence others not to buy from the company.
These four stages represent the downward spiral that begins with a dissatisfied customer and ends with a lost customer.
The research report uses a tree to show where customers get lost through the various stages of disloyalty. The tree starts with 1200 customers. The first stage (two branches) shows that 960 customers (80%) have no problem and 240 have a problem. Of the 240, (the second stage with two branches) there are 48 customers with a problem (this represents 20% of those with a problem who don't tell anyone and start down the path to disloyalty). Of the 192 that do tell someone (the third stage with two branches) 86 get excellent results (45%) and 102 do not get excellent results and start on the path to disloyalty. Finally in the fourth stage there are two branches that show half of those who received excellent response decide to purchase again and the other half chose not to repurchase. When all of these probabilities are combined there are 197 customers out of the original 1200 (16.4%) who end up on the road to disloyalty.
One of the obvious conclusions that can be drawn from this discussion is when companies do not handle complaints very well they are accelerating the decline from dissatisfaction to disloyalty. The data used in the research paper to create the probabilities was from a client and hence has some validity. While these probabilities represent the performance of just one company, the conclusion drawn by Dr. lockhart makes sense.
The bottom line is that managing customer complaints well appears to have a dramatic positive effect on customers with the implication that the company also benefits in terms of reducing the number of customers that may become disloyal. The challenge for companies is to examine the magnitude of these four stages that lead to disloyalty. One way to think about these four stages is to see them as cracks in the organizational structure. Then it becomes a management problem of how best to fill the cracks.
Saturday, April 17, 2010
More About Customers as Assets
One of the goals of The Customer Institute is to publish a book which describes customers as assets and how to manage those assets. When customers are viewed as assets they take on a different perspective. For example Apple computer has taken the position that customers are assets and have developed them to the point where they can introduce a new product, such as the iPad and almost guarantee huge sales. Ben Fowler wrote an interesting piece dated April 6, 2010 in his blog (voiceofcustomerguru). Customers of Apple respond to Apple product announcements with little hesitation because they believe that Apple products deliver high quality.
Compare Apple to US automobile manufacturers during the 60s and 70s. They built cars with great styling and innovation but the product quality was inferior to those being sold by the Japanese whose products had less style and innovations but superior quality. The US automakers damaged their customer asset to the point that even today when their product quality is equal to the Japanese, they must offer incentives and lower prices to get sales.
The US economy has changed in the last 50 years. Whereas 50 years ago the size of manufacturing was twice the size of consumer service. Today the ratio is the same but with consumer service twice the size of manufacturing. Consumer service requires a different accounting system than the one used for manufacturing. When cars are sold there is an immediate transfer of asset from the car manufacturer to the new owner. The asset transfer is complete.
When we are dealing with the customer asset, we need to look at the value of that asset over time rather than in a single time period. There are have a number of books and articles written about measuring the value of a customer. One book that has been around for a while is "Managing Customer Value: Creating Quality and Service That Customers Can See" by Bradley Gale. The typical calculation of long-term customer value is based on the average life of a typical customer. If the customer life is three years, the value is based on three years. However, many of the books and articles written about calculating the value of a customer have not dealt with the value as an asset and its implications when looked at from an accounting perspective.
Note the following example and some of the accounting discussion is being done without the oversight of an accountant and must be viewed with some scepticism.
There is an excellent example of this weakness of viewing the customer asset in a book by C. Fornell titled "The Satisfied Customer: Winners and Losers in the Battle for Buyer Preference." The example the author uses examines the case where it costs $1000 to acquire a customer. If the customer lifetime is 3 years, the net income for those 3 years is -$100. If the company has acquired 1000 new customers for the year, the cost of acquisition is $1,000,000 and the net income from those new customers is $300,000. However, that is not the way the accounting system would report the performance of the company. The accounting system would show a loss of $700 for each customer acquired for the first year or a total loss of $700,000 for the 1000 new customers. The second year an additional 1000 new customers are acquired for another $1,000,000. This year the total sales is $600,000 so that the total loss for the year is only $400,000. When you include the third year the lost is $100,000 for each and every year thereafter as long as the average customer lifetime is 3 years.
The customer asset must be viewed in the light of the value to acquire it and the revenue expected from each customer. One of the keys to building the customer asset is consistent performance and value similar to Apple. Toyota has just dramatically reduced it customer asset by mismanaging its communications with its customers.
The bottom line is that customer retention is a key to success in the consumer service marketplace and the foundation for building the customer asset. Companies need to know the length of the average customer lifetime before they start a campaign to acquire new customers. What is usually missing in many companies is the cost to acquire a customer and the average customer lifetime. We have been taking the wrong measurements.
This analysis does not examine the process of building the customer asset. We will have to investigate further to understand how Apple has achieved so much asset value from its customers.
Compare Apple to US automobile manufacturers during the 60s and 70s. They built cars with great styling and innovation but the product quality was inferior to those being sold by the Japanese whose products had less style and innovations but superior quality. The US automakers damaged their customer asset to the point that even today when their product quality is equal to the Japanese, they must offer incentives and lower prices to get sales.
The US economy has changed in the last 50 years. Whereas 50 years ago the size of manufacturing was twice the size of consumer service. Today the ratio is the same but with consumer service twice the size of manufacturing. Consumer service requires a different accounting system than the one used for manufacturing. When cars are sold there is an immediate transfer of asset from the car manufacturer to the new owner. The asset transfer is complete.
When we are dealing with the customer asset, we need to look at the value of that asset over time rather than in a single time period. There are have a number of books and articles written about measuring the value of a customer. One book that has been around for a while is "Managing Customer Value: Creating Quality and Service That Customers Can See" by Bradley Gale. The typical calculation of long-term customer value is based on the average life of a typical customer. If the customer life is three years, the value is based on three years. However, many of the books and articles written about calculating the value of a customer have not dealt with the value as an asset and its implications when looked at from an accounting perspective.
Note the following example and some of the accounting discussion is being done without the oversight of an accountant and must be viewed with some scepticism.
There is an excellent example of this weakness of viewing the customer asset in a book by C. Fornell titled "The Satisfied Customer: Winners and Losers in the Battle for Buyer Preference." The example the author uses examines the case where it costs $1000 to acquire a customer. If the customer lifetime is 3 years, the net income for those 3 years is -$100. If the company has acquired 1000 new customers for the year, the cost of acquisition is $1,000,000 and the net income from those new customers is $300,000. However, that is not the way the accounting system would report the performance of the company. The accounting system would show a loss of $700 for each customer acquired for the first year or a total loss of $700,000 for the 1000 new customers. The second year an additional 1000 new customers are acquired for another $1,000,000. This year the total sales is $600,000 so that the total loss for the year is only $400,000. When you include the third year the lost is $100,000 for each and every year thereafter as long as the average customer lifetime is 3 years.
The customer asset must be viewed in the light of the value to acquire it and the revenue expected from each customer. One of the keys to building the customer asset is consistent performance and value similar to Apple. Toyota has just dramatically reduced it customer asset by mismanaging its communications with its customers.
The bottom line is that customer retention is a key to success in the consumer service marketplace and the foundation for building the customer asset. Companies need to know the length of the average customer lifetime before they start a campaign to acquire new customers. What is usually missing in many companies is the cost to acquire a customer and the average customer lifetime. We have been taking the wrong measurements.
This analysis does not examine the process of building the customer asset. We will have to investigate further to understand how Apple has achieved so much asset value from its customers.
Monday, April 12, 2010
Benchmarks - How Good Are They?
In the latest issue of Quirk's Marketing Research Review (April 2010), there is a survey of researchers regarding benchmarking. The survey was performed in the Spring of 2009 with 97 responses from people involved in market research in their organizations (83 have a designated market research function). The survey was performed by Jennifer Van de Meulebroecke and Michele Sims both members of the staff at TRC Market Research in Fort Washington, PA. The researchers represented many markets including insurance, utilities, high-tech, health care and financial services.
The researchers noted that:
1. 75% of the researchers collected benchmark data as part of an internal study,
2. 56% of the researchers collected benchmark data separately or at a different time than other studies. Some also use an outside vendor for assistance.
3. 56% of the researchers used a syndicated source for their benchmark data.
The research went farther by asking the researchers to focus specifically on benchmarking data and describe their confidence in making comparisons for their company with benchmark data. The results indicated that 75% of the researchers who had less than 11 years in market research had confidence in using external benchmarking data; whereas only 58% of those with more than 11 years in market research had confidence in using the external benchmarking data for comparisons. The conclusion drawn from this piece of information is that it appears that the longer people are in market research, the less trust they have in using the external benchmark data to draw comparisons.
Since there are such low scores with respect to using external benchmark data, the question is what are the factors that people should be aware before using external benchmark data. The survey found the following factors and are ranked in order of importance by those who were surveyed:
1. 91% were concerned about the consistency of the scales and responses,
2. 83% were concerned with consistent question wording,
3. 77% were concerned with consistent screening,
4. 67% were concerned with the method of collecting the data (web, phone, etc),
5. 58% were concerned with type of sample that was used, and
6. 51% were concerned with the time period for data collection.
As an editorial comment I would note that many companies put extreme value on industry benchmarks. I had a consulting assignment several years ago with a high-tech company that had the lowest scores on their industry benchmark. The executives and managers were very concerned about their score. They believed, and rightly so, that thefact that the benchmark that showed they had the lowest scores in their industry would impact their sales. They asked for my help and within 3 years they were tied at the top of the industry benchmark. The problem was that they were scored low but did not have enough information to know where to make changes to their product nor support. Once we captured the information it was only a matter of time before they moved to the top.
The bottom line is that benchmarks are becoming more and more important to companies. Today many companies use benchmark data to assess their market position without understanding how the benchmark was created. In addition, the companies do not have the detail information necessary to accurately evaluate the meaning of the benchmark scores. The lesson is benchmarks are very valuable when used properly but can be VERY misleading when not properly understood.
The researchers noted that:
1. 75% of the researchers collected benchmark data as part of an internal study,
2. 56% of the researchers collected benchmark data separately or at a different time than other studies. Some also use an outside vendor for assistance.
3. 56% of the researchers used a syndicated source for their benchmark data.
The research went farther by asking the researchers to focus specifically on benchmarking data and describe their confidence in making comparisons for their company with benchmark data. The results indicated that 75% of the researchers who had less than 11 years in market research had confidence in using external benchmarking data; whereas only 58% of those with more than 11 years in market research had confidence in using the external benchmarking data for comparisons. The conclusion drawn from this piece of information is that it appears that the longer people are in market research, the less trust they have in using the external benchmark data to draw comparisons.
Since there are such low scores with respect to using external benchmark data, the question is what are the factors that people should be aware before using external benchmark data. The survey found the following factors and are ranked in order of importance by those who were surveyed:
1. 91% were concerned about the consistency of the scales and responses,
2. 83% were concerned with consistent question wording,
3. 77% were concerned with consistent screening,
4. 67% were concerned with the method of collecting the data (web, phone, etc),
5. 58% were concerned with type of sample that was used, and
6. 51% were concerned with the time period for data collection.
As an editorial comment I would note that many companies put extreme value on industry benchmarks. I had a consulting assignment several years ago with a high-tech company that had the lowest scores on their industry benchmark. The executives and managers were very concerned about their score. They believed, and rightly so, that thefact that the benchmark that showed they had the lowest scores in their industry would impact their sales. They asked for my help and within 3 years they were tied at the top of the industry benchmark. The problem was that they were scored low but did not have enough information to know where to make changes to their product nor support. Once we captured the information it was only a matter of time before they moved to the top.
The bottom line is that benchmarks are becoming more and more important to companies. Today many companies use benchmark data to assess their market position without understanding how the benchmark was created. In addition, the companies do not have the detail information necessary to accurately evaluate the meaning of the benchmark scores. The lesson is benchmarks are very valuable when used properly but can be VERY misleading when not properly understood.
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