Calculating ROI on the customer experience typically takes the blind faith approach, where ROI on customer service is considered a given, and the sophisticated approach, where predictive models explain the links between service attributes, customer satisfaction and profitability. Such models can, in fact, be valuable as a means for understanding the associations among different service and profit factors. They can also provide insight into how service attributes interact with each other to influence customer perceptions. A major drawback, however, is that these models tend to have too many moving parts to function as a practical, day-to-day business tool, give the appearance of being far more precise than they actually are, and may be too sophisticated for some audiences.
Sometime managers need a simpler, more intuitive approach to estimating ROI on customer service.
First let me suggest the proposition that every time a company and service provider interact the customer learns something positive or negative and adjusts their behavior, again positive or negative based on what they learn. This is a behavioral approach to managing the customer experience, that by managing customer behaviors in profitable ways, service providers can maximize return on investment in the customer experience.
Using this behavior approach as a model, it possible to construct a simple intuitive ROI estimate of the customer experience.
List customer behaviors with financial implications
The first step in this methodology is to list all customer behaviors that directly drive revenues or costs. Ask yourself, “What specifically, do we want customers to do more or less of?” Don’t include attitudes, such as satisfaction, or feelings such as delight – only include empirically measureable behaviors such as purchase more, purchase more frequently, call for support less often, use more profitable channels, return merchandise less frequently, etc.
Before moving on to the next step, review this list and eliminate any customer behaviors that cannot be influenced through service interactions.
List service attributes that likely influence customer behaviors
Next, work backwards making a second list of specific , measureable service attributes that likely influence desired customer behaviors. This list should only include attributes for which there is a realistic cause and effect relationship between the service attribute and customer behavior. Ask yourself, “What can we (across all service channels) do more of, less of, or do differently to influence customer behaviors?” If it can’t be measured, if it can’t be trained (or programmed) or if it has no likely effect on measureable customer behaviors that affect profit, it should be removed from the list.
Consider how to influence desired customer behaviors (systems, skills, incentives, measurement & rewards)
Now, consider what specific systems, knowledge and skills are required to provide the service that will influence desired customer behaviors. Consider what employee incentives will be most effective in reinforcing the use of those skills and what measurement tools need to be in place to gather the metrics to trigger appropriate rewards.
Link list of customer behaviors to costs and revenues (incremental change)
Finally, link the first list (customer behaviors) to costs and revenues. To do this, calculate the financial impact of an incremental change in each item. For example, what would be the effect on revenue of increasing the average customer purchase by one dollar? What would be the effect on costs if the volume of complaints to call centers were reduced by five percentage points? It quickly becomes clear that even a small change in some customer behaviors can have a substantial financial impact. It also becomes clear which service changes will have the biggest effect.
Thus far you have identified the customer behaviors you want to change, the general influence of each behavior on revenue or cost, and the dollar value of an incremental change in each behavior.
The major element missing from the formula is magnitude. How much change can the company expect to create? Can complaints be reduced by 1%, 5%, 10%? Will average purchase amounts increase by 50 cents? Ten dollars?
Also missing is the interaction among different variables. For example, aggressive up-selling may lead to a 10% increase in the average transaction amount, but it could also lead to a 2% increase in customer turnover, which might counteract the benefit.
The only way to answer these questions is to experiment.
Finally, this method excludes word of mouth customer behavior. In this ad of social media, increasing word of mouth (positive or negative) is an important customer behavior to manage. It’s been excluded from this tool do difficultly empirically measuring its benefits. See the attached post for a description of word of mouth measurement.
What if I told you that after all your efforts with marketing (product, positioning and price), there is a one-in-ten chance the branch representatives will undermine the sale?
Now more than ever, it is critical for banks to establish themselves as the primary provider of financial services, not only for deposit accounts but across a variety of financial products and services. Increasing the average products per customer will require a strategic approach to both product design and marketing. However, at the end of this strategic marketing process, there is the human element, where prospective customers must interact with bank employees to complete the sales process.
As part of our services to our clients, Kinesis tracks purchase intent as a result of in-branch sales presentations. According to our research, 10% of in-branch sales presentations observed by mystery shoppers, result in negative purchase intent.
What do these 10% failed sales presentations look like?
Here are some quotes describing the experience:
“There was no personal attention. The banker did not seem to care if I was there or not. At the teller line, there was only one teller that seemed to care that there were several people waiting. No one moved with a sense of urgency. There was no communication materials provided.”
Here’s another example…
“It was painfully obvious that the banker was lacking basic knowledge of the accounts.”
“Brian did not give the impression that he wanted my business. He did not stand up and shake my hand when I went over to his desk. He very rarely made eye contact. I felt like he was just going through the motions. He did not ask for my name or address me by my name. He told me about checking account products but failed to inquire about my situation or determine what needs I have or might have in the future. He did not wrap up the recommendation by going over everything nor did he ask for my business. He did not thank me for coming in.”
In contrast, here is what the shops with positive intent look like:
“The appearance of the bank was comfortable and very busy in a good way. The customers were getting tended to and the associates had the customers’ best interests in mind. The response time was amazing and I felt as if the associate was sincere about wanting me as a customer, but he was not pushy or demanding about it.”
Now…after all the effort and expense of a strategic cross-sell strategy, which of the above experiences do you want your customers to encounter?
Would it be acceptable to you as a marketer to at the end of a strategic marketing campaign, have 10% of the sales presentations undermine its success?
These are rhetorical questions.
Time and time again, in study after study, we consistently observe that purchase intent is driven by two dimensions of the customer experience: reliability and empathy. Customers want bankers who care about them and their needs and have the ability to satisfy those needs. Specifically, our research suggests the following behaviors are strongly related to purchase intent:
- Greeting/Stand to Greet/Acknowledge Wait
- Interest in Helping/Offer Assistance
- Discuss Benefits/Solutions
- Promised Services Get Done
- Express Appreciation/Gracious
- Personalized Comment (such as, How are you?)
- Listen Attentively/Undivided Attention
As part of any strategic marketing campaign to both bring in new customers as well as increase wallet share of existing customers, it is incumbent on the institution to install appropriate customer experience training, sales and service monitoring, linked with incentives and rewards structures to motivate sales and service behaviors which drive purchase intent.
Increasingly banks must operate in a multi-channel environment. While the changing role of the branch, combined with automated channels such as online and mobile, are getting a lot of attention, there remains a key role for the contact center in delivering an effective customer experience. Central to this key role is designing an effective customer experience, comprised of the right sales and service behaviors – those which influence customer attitudes and behaviors in a profitable way yielding the most return on investment.
To provide direction with respect to what sales and service behaviors will yield the most return on investment, Kinesis conducted a series of mystery shops to identify which sales and service behaviors have the most influence on purchase intent. In addition to observing specific sales and service behaviors, mystery shoppers were also asked to rate how the call would have influenced their purchase intent if they had been a real customer. This purchase intent rating was then used as means of calculating the strength of the relationship between each behavior and purchase intent.
To determine the relationship between these service attributes and purchase intent, the data for these different studies was cross-tabulated by the purchase intent rating and subjected to significance testing. [i]
When the percentage of calls in which purchase intent significantly increased is tested against the percentage of calls where purchase intent significantly decreased, nearly all the sales and service attributes are statistically significant at or above a 95% confidence level.
|Significantly Increased||Significantly Decreased||Test Statistic|
|Explanations easy to understand||99%||45%||9.0|
|When thanked, respond graciously||98%||42%||8.5|
|Friendly demeanor / pleasant voice||100%||60%||8.4|
|Express appreciation for interest / thank you for business||92%||20%||8.3|
|Ask probing questions||79%||10%||6.4|
|Offer further assistance||85%||25%||6.2|
|Speak clearly and avoid bank jargon||98%||68%||5.8|
|Listen attentively to your needs||80%||25%||5.3|
|Mention other bank product||99%||75%||5.3|
|Invite you to visit branch||64%||10%||4.6|
|Explain the value of banking with bank||57%||5%||4.4|
|Offer to mail material / mention website||66%||20%||4.3|
|Ask your name||68%||25%||3.8|
|Ask for your business / close the sale||57%||21%||2.9|
|If no one available to assist you, offered options||100%||0%||2.2|
The differences between the highest and lowest purchase intent for product knowledge and ease to understanding explanations are the most significant, while a professional greeting is the least significant.
Dividing these behaviors into rough quartiles and comparing them side-by-side, reveals some interesting observations:
Explanations easy to understand
When thanked, respond graciously
Friendly demeanor / pleasant voice
Express appreciation for interest / thank you for business
Ask probing questions
Offer further assistance
Speak clearly and avoid bank jargon
When thanked, employee respond graciously
|Listen attentively to your needs
Mention other bank product
Invite you to visit branch
Explain the value of banking with bank
Offer to mail material / mention website
|Ask your name
Ask for your business / close the sale
If no one available to assist you, offered options
The attributes with the most significant differences between high and low purchase intent ratings appear to be those associated with reliability and empathy. It appears mystery shoppers valued such “core” attributes as product knowledge or interest/enthusiasm for the customer. They seem to be less concerned with more peripheral service attributes, such as asking for names, etc. Influencing purchase intent is not as simple as merely using the customer’s name or answering the phone within a short period of time. Rather it is a much more challenging undertaking of being competent in your job and having the customer’s best interests at heart.
[i] Significance testing determines if any differences observed are the result of actual differences in the populations measured rather than the result of normal variation. Without getting into too much detail, significance testing produces a test statistic to determine the probability that differences observed are statistically significant. A test statistic above 1.96 equates to a 95% confidence level, which means there is a 95% chance any differences observed are the result of actual differences in the populations measured rather than normal variation. For all practical purposes a test statistic over 3.1 means there is 100% chance the differences observed are statistically significant (although in reality the probability never reaches 100%). Finally, in interpreting the following analysis, it is important note that test statistics are not lineal. A test statistic of two is not twice as significant as a test statistic of one. The influence on significance decreases as the test statistic increases. However, the test statistic does give us an opportunity to rank the service attributes by their statistical significance.
I recently came across a very intriguing bit of research that suggests the benefits of investments in the customer experience in terms of shareholder return.
Great customer service processes and people are not built overnight. They take years of investment to cultivate. Unfortunately, for some publically traded companies, the short-term demands of Wall Street make such investment difficult. The demands of investors to meet earnings estimates for the next quarter can make it difficult for managers to invest in the customer experience – the payback is too slow and uncertain.
Stockholders have little patience nowadays with investments that do not show a clear and quick return. To ensure that managers are acting in the owners’ interests, management incentives are more frequently tied to quarterly financial performance than to difficult-to-measure variables like customer loyalty.
Given great customer experiences are not built overnight, they are constantly at risk of budget cuts by managers who would boost short term earning at their expense. Service initiatives have a tendency to come and go in large companies before they have a chance to prove their worth, resulting in customer frustration, employee cynicism and widespread service mediocrity.
Service gurus talk about the need for “investor loyalty” as a counterbalance to customer loyalty, but that requires a visionary, motivated and stable management team who can convince investors to look farther ahead.
Easier said than done, right? How does one make the case for investments in the customer experience in an environment that demands making the next quarters numbers?
Jim Picoult, founder of Watermark Consulting, has an answer. Jim has created a stock index based on Forester’s annual Customer Experience Index (CXI). Jim calculated the returns of two hypothetical portfolios consisting of the top and bottom 10 publicly traded companies in Forester’s CXI for a six year period ending in 2012. Each year he rebalanced the two portfolios based on Forester’s new rankings. The portfolio comprised of companies ranked in Forester’s top 10 yielded a cumulative return of 43%, compared to 14.5% for the S&P 500. The portfolio containing the bottom 10, yielded a cumulative return of negative 33.9% – it lost a third of its value.
Now, correlation is not causation, and there are a lot of factors at play here. But clearly the managers of firms in the portfolio of Forester’s top 10 were able to both deliver shareholder value and invest in the customer experience.
It all comes down to thinking of the customer as an asset in which to invest and realize a return.