Customers are the most important part of any business, and keeping them happy should be at the top of your list of priorities. If your organization is among those that have created customer experience maps, kudos to you and your team! If not, and this is an itch you want to scratch, read on for five (5) tips to help you undertake this important initiative.
Before we offer advice for mapping the customer experience, it might be useful to make sure we’re all on the same page in terms of what we mean by customer experience. At VisionEdge Marketing, when we refer to customer experience we mean the points of interaction between the customer and an organization. These touch points include, but are not limited to, interactions associated with pricing, purchasing, servicing, payment/billing, support, and delivery of your organizations offerings (goods and/or services).
How customers evaluate their experience is based on their perception of the actual performance of the organization at that point of interaction compared to the customer’s expectation. In 2005, James Allen from the Harvard Business School revealed that while 80% of businesses state that they offer a great customer experience, only about 8% of customers feel similarly about their experience. Understanding this perception versus the expectation, and the gaps across all experiences, enables you to create customer experience performance targets and key performance indicators.
Customer experience mapping is a vehicle for capturing the perceptions versus the expectations across all points of interaction, ideally for each customer segment and/or persona. The mapping process should enable you to develop processes and skills designed to deliver an experience that sets your organization apart in the eyes of your customers, hopefully resulting in customer loyalty and becoming advocates for your goods/services.
Many organizations often mistake creating a process map with creating a customer experience map. While similar, their focus is quite different. A process map describes your company’s internal processes, functions, and activities and generally uses the company’s internal language and jargon. A customer experience map describes the customer experience in, and only in, the customer’s language. What makes customer experience mapping challenging is the fact that the customer experience is typically quite complex, because it cuts across divisions, departments, and functions.
Here are five key steps to help you create your customer experience map:
1. Start with the universal touch points that can be applied across all your customers (you can create more specific experience maps as time goes on)
2. Make a list of all the touch points. For each touch point write a description, method of interaction, and customer expectation. We have found that this step is best accomplished by:
- Involving as many people as necessary, including members of your customer advisory boards, to identify all touch points
- Holding working sessions and conducting interviews to capture and incorporate the expected and actual emotional, experiential, and functional experiences for each touch point
3. Document your learnings and produce a visual illustration (map)
4. Use the map to identify areas working well and those that need improvement. Focus on those areas that are known as “moments of truth,” those crucial interactions that determine whether the customer becomes or remains loyal
5. Build a plan to address James Allen’s “Three D’s,” which he believes enables organizations to offer an exceptional customer experience:
- Design the correct incentive for the correctly identified consumer, offered in an enticing environment.
- Deliver the proposed experience by focusing the entire team across various functions.
- Develop consistency in execution.
Sometimes organizations need help with this, which is why there are experts out there! Don’t be afraid to ask for help–this is an area you do not want to ignore.
We know–models can be intimidating. But as the need to add analytics and science to our work continues to increase, models have become one of the primary vehicles every marketer needs to know how to develop and leverage. If you’ve already dived into the deep end on models, congratulations. On the other hand, if you’re just dipping your toe into the water, have no fear, because while there may be a bit of a current, it is time to venture forth.
Mathematical models help us describe and explain a “system,” such as a market segment or ecosystem. These models enable us to study the effects of different actions, so we can begin to make predictions about behavior, such as purchasing behavior. There are all kinds of mathematical models-statistical models, differential equations, and game theory.
Regardless of the type, all use data to transform an abstract structure into something we can more concretely manage, test, and manipulate. As the mounds of data pile up, it’s easy to lose sight of data application. Because data has become so prolific, you must first be clear about the scope of the model and the associated data sources before constructing any model.
So you’re ready to take the plunge–good for you! So, what models should be part of every marketer’s plan? Whether a novice or a master, we believe that every marketer must be able to build and employ at least four models:
- Customer Buying Model: Illustrates the purchasing decision journey for various customers (segments or persona based) to support pipeline engineering, content, touch point and channel decisions.
- Market Segmentation or Market Model: Provides the vehicle to evaluate the attractiveness of segments, market, or targets. More about this in today’s KeyPoint MPM section.
- Opportunity Scoring Model: Enables marketing and sales to agree on when opportunities are sales worthy and sales ready.
- Campaign Lift Model: Estimates the impact of a particular campaign on the buying behavior.
These four models are an excellent starting point for those of you who are just beginning to incorporate models into your marketing initiatives. For those who have already developed models within your marketing organization, we would love to know whether you have conquered these four, or even whether you agree these four should be at the top of the list. As always, we want to know what you think, so comment or tweet us with your response!
Many companies are developing opportunity scoring models which essentially assign a predetermined numerical score to specific behaviors or statuses within a database. The purpose of opportunity scoring is help sales people know which opportunities are sales ready and worthy, and therefore take priority. Often variables such as title, company, and industry, serve as the basis for the scoring model. However, behaviors can be used too, such as the completion of a contact form, visiting a particular page on the website, participating or viewing a demo, etc. Contextual data adds another dimension to the model by weaving in predisposition information that reflects content, timing and frequency-for example what products they currently use, the last time they purchased, their complete buying history, the types of keywords they used in their search, etc.
Keep in mind, timing is everything. To be effective, contextual data must be delivered to the right person, at the right time, within an actionable context. For example, the date of a key customer’s contract renewal is posted in your CRM system all year long, but that doesn’t mean you’ll remember or even see it. Think how much more useful that data becomes when your system automatically alerts you to the fact that it’s the customer’s renewal date. Sending email messages about renewals too early just creates noise at best and at worst suggests you don’t know their renewal date. Customers are more likely to respond to call to action when it is in context of their workflow. Communication that is contextual is more personal and as a result feels more authentic, shows value, and leads customers want to act. As a result, you can reduce the cost of customer acquisition and the cost of sales.
The end goal of contextual data is to connect with the buyer when they are most predisposed to buy. As a result, you can use contextual data to help build propensity to purchase models, for prioritizing opportunities to support opportunity scoring, to develop more personalized messages, and select the best mix of channels.
This same concept of contextual data can be used to build propensity to purchase models. By identifying the winning experiences associated with a particular segment, you can use this information to craft more relevant messages to similar targets to increase uptake.
Personalization is a compelling and challenging proposition. It’s a moving target and therefore requires a test and learn approach. By adding contextual data into the process you can make your personalization efforts more effective and more relevant.
Companies who want to retain or expand their relationships with existing customers are finding that measuring and modeling customer loyalty is very valuable. We were recently asked “Do you need to measure loyalty if you are measuring retention-aren’t they the same thing?” Our answer, no, they are not the same thing, and you may need both.
Retention is a measure of whether an existing customer continues to do business with you. That is not to be confused with loyalty, which measures a customer’s predisposition to select a business entity as a preference, and indicates a certain resistance to competitors. Loyalty is a behavioral disposition that suggests that a customer will consistently respond favorably toward a brand/company, and also suggests the willingness to engage. As you can see, there is a distinction and it’s important to understand that a customer who continues to do business with you may be retained, but not necessarily loyal.
Responding favorably covers a lot of territory-from passively choosing to remain a customer, to actively choosing to advocate for a brand/company. Therefore, while measuring retention, once you define what a customer is in terms of tenure, it is a matter of counting. Loyalty takes a bit more sophisticated measurement and needs to take into account three potential behavioral responses if you are going to use the concept to build a model:
- Expansion–the likelihood the customer will increase their level of business, such as by purchasing more of the same product or other products in your portfolio
- Influence–the degree to which they can be influenced by the company in a way that positively impacts the company, such as seeking out advice, paying online, complying with new policies
- Advocacy–the extent to which a customer is willing to actively promote the company, such as online reviews, supporting the company’s position on an issue, participation in case studies, serving as a reference, or making referrals.
Note: The Net Promoter Score (NPS) methodology attempts to account for these 3 behaviors, but the primary goal of this score is to help you ascertain the number of promoters vs. detractors.
You will want to determine which of these behaviors (it can be all of them) best define loyalty for your company. If you don’t know, the answers to these five questions will help you get started:
- What is the ideal customer for your company? What do they do/not do? What does a less-than-ideal customer look like?
- What does your company want from its relationship with customers and why?
- What can customers do to support the company’s mission?
- What can customers do to help the company improve service and reduce the cost to serve?
- What can customers do to reduce the cost of doing business with them?
You may want to engage a number of stakeholders in conversations around these questions. Once you determine the behaviors that define loyalty, you can build a model and begin to measure loyalty. It may be necessary to take different customer segments into account, and as a result you may need more than one model. To validate the model, you may need to conduct some research with customers who meet the loyalty criteria as well as customers you believe do not. Then, set about defining how you will use the model to measure and improve loyalty.
Customer loyalty is an intangible but extremely valuable company asset. By distinguishing retention from loyalty you can begin to understand the customer experiences, interactions, perceptions and attitudes that drive and impact loyalty.
Many marketing organizations today have an influencer marketing strategy. The purpose of this strategy is to help with customer acquisition (number and/or rate) and rate of product adoption. The findings in the 2013 Influencer Marketing Survey support this perspective, “influencer marketing is seen as a customer acquisition and lead generation practice not a brand exercise.”
This strategy entails establishing and tapping relationships with people that are perceived by the market and customer to have the ability or power to affect or sway other people’s thinking or actions. Influencers exist within every ecosystem – these can be members of the press/blog community, analysts and industry thought leaders, industry experts, trusted advisors, etc. The breadth, quantity and quality of your influencers will impact the success of this strategy.
Before we jump into how to measure influence marketing, we’d like to respond to a question we’re frequently asked, “What is the difference between influencer marketing and public relations?” The answer to this could be its own article, so to quickly explain the difference, we turned to our friend Chris Aarons (@Chris_Aarons), an expert in implementing influencer marketing strategies.
Chris says, “The simplest answer is that public relations is about communicating your messages to and with members of the press (and some PR firms include bloggers as well) to spread information or news. Whereas, influencer marketing focuses on identifying and securing credible third-parties with extensive networks, who may not necessarily be members of the press, to drive engagement and/or marketing objectives.” We’ll leave it to you to tweet with Chris on how you feel about this explanation!
Back to influencer strategy management… Relevant metrics include:
- Activity-based: number of influencers, types of influencers, and the degree of engagement by each influencer
- Pipeline: deals and wins, influencer contributed lead and acquisition cost, sales cycle impact, and influencer lift
Ultimately, what you want to know is whether influence or sway is impacting customer acquisition, and if so, how much and how fast.
Should this be a viable strategy for your organization, you may want to think beyond counting, and create a way to measure influence. In the social world, various organizations are creating influence metrics. But influence occurs both on and off line, which means you need to be able to measure influence/sway beyond the “social digital world.” As with many key performance metrics, an influence metric is comprised of several measures.
So how might we construct such a metric? Conceptually we can posit that influence is derived from two variables, quality and impact. The equation would look like:
Influence = Quality (%) x Impact (#)
In addition, factors that affect each of these variables include the following:
- What percentage of the desired influencers participated?
- How prominently did they feature your company/product? Assign percentages to these or others you if you prefer [Top billing or stand-alone article/blog, subject line mention or tweet, quote in general or related article, participation in LinkedIn Discussion]
- What is the overall sentiment/tone of the influencers’ content/conversation/discussion? Assign a percentage to each of these positive, negative, neutral
- Quantity – the total number of tweets, shares, likes, comments, click throughs, etc. generated by the influencers
- Penetration – how many of the targeted markets/communities were reached (for example – LinkedIn Groups, click throughs to links)
Add up your quality factors, add up your impact factors, and then multiply the two sums. Start by collecting the data and establishing your base line. Monitor the change in your influence metric and analyze the impact of each factor on the score. Once you complete these steps, it will be necessary to evaluate the relationship between the influence score and your number and rate of customer acquisition.
In his book, The Effective Executive, Peter Drucker explained the difference between efficiency and effectiveness: “Efficiency is doing things right. Effectiveness is doing the right things.” He strongly advised focusing first on effectiveness before efficiency. Along with outcome-based and leading-indicators metrics, Marketers also need both efficiency and effectiveness metrics. Here’s an easy way to distinguish whether your metric is one or the other:
- If the metric is measuring how well you squeeze out waste or cost or measure maximum output for input, it’s most likely an efficiency metric. Marketing spend, ROI, and cost/per lead, lead/rep are examples of efficiency metrics.
- If the metric is measuring how well you are contributing to or producing a desired result, it is most likely an effectiveness metric. Share of preference, share of wallet, products/customers are examples of effectiveness metrics.
As we have learned from over a decade of research on marketing metrics, many marketers are doing a good job of establishing, monitoring, and managing efficiency metrics and not as good of a job with developing, measuring, and managing effectiveness metrics.
This propensity to focus on efficiency metrics ultimately creates a problem for marketing. You can be improving efficiency, which has nothing to do with whether or not what you are currently doing is the right thing to do, while not actually becoming less effective. Effectiveness is about achieving the right result, or being on the right path. When we are positively impacting and contributing to the right result, then we earn our right to participate in strategic conversations.
It may be easier to identify, track and manage efficiency metrics but that may not be the only reason we see more efficiency related metrics. Many people assume that they are on the right track so if and when there is a problem, they address it by trying to make the process more efficient without questioning whether they are going in the right direction. But if you are going in the wrong direction, becoming more efficient will actually make the problem worse. For example, let’s say your company wants to grow its revenue by some amount. As a marketer, you believe you can affect this by producing some additional business from existing customers. So, you are monitoring and improving the inquiries, deals, cost per new deal, etc. The company is growing but its market share is declining. Why, because the growth opportunity is really outside the existing customer segment. So while marketing is becoming more and more efficient at generating business from existing customers, the company’s market share is actually declining and the competitors are achieving greater market dominance.
What’s really important is effectiveness. In the end, it doesn’t matter if your business is spending the least amount possible or your demand-generation initiatives are streamlined. What matters is whether marketing is solving the right problems and moving the right business needles.
Before you start thinking about how to improve your efficiency, step back and think about how marketing is expected to move the needle and measure its effectiveness. Don’t misunderstand, efficiency is extremely important and you will need efficiency metrics. Improving efficiency can make a difference, but only if you’re on the right path. And the only way to know that is to have effectiveness metrics in place as well. Efficiency is important, but powerless without effectiveness. Effectiveness opens the door for efficiency.