3 items tagged "customer intelligence"

  • Before jumping to conclusions, ask 'why'?

    Before jumping to conclusions, ask 'why'?

    An account executive on your sales team, Jen, is chatting with a prospect. The conversation is going well. The prospect doesn’t seem to be evaluating any other vendors.

    And then they say this: “Talk to me about your SMS marketing tool.”

    Your product doesn’t include such a tool—and for good reason. Your product managers have done their research. There’s no real customer need or demand for it.

    Nevertheless, one of your competitors launched a flashy SMS marketing tool six months ago, and ever since then, they’ve been using it to put Jen and her peers in a defensive position. They tell prospects to bring this topic up in hopes that your sellers will get flustered, thus casting doubt on the quality of your product.

    Apparently, this is a competitive opportunity after all.

    So, how should Jen respond to the prospect’s request? Should she explain why your product doesn’t have the thing they’re looking for? Should she try to change the way the prospect thinks?

    Nope. She should calmly respond with a question: “Why do you need an SMS marketing tool?”

    The goal is to help the prospect help themselves—to gently nudge them towards the realization that they do not, in fact, need an SMS marketing tool for what they’re trying to achieve. This realization alone will not eliminate the competitor from the evaluation, but at the very least, it will keep them from gaining the upper hand and make it clear that Jen has the prospect’s best interests at heart.

    Chris Pope, a former member of the Crayon sales team who is now our Senior Director of Strategy, added his two cents: “When it comes to objections and landmines, your sellers need to get to the root of your buyers’ problems. If a buyer is mesmerized by flashy features that don't solve their problems, it's the seller’s job to direct them back to the reasons they’re speaking in the first place. That’s the power of asking why: It steers the conversation back in your favor in a non-salesy way.”

    Obviously, the primary benefit of this tactic is that it will help your sellers win more competitive deals. For those of you with access to a call recording tool like Gong, the secondary benefit is that it will help you, as a product marketer, better understand your customers.

    See, if you can get your sellers to ask “Why?” more often, then you’ll soon have a library of invaluable call snippets—snippets in which your customers really get to the heart of the pain points they’re experiencing. With this data, you’ll be better equipped to position and promote your products, your product managers will be better equipped to innovate, your content marketers will be better equipped to attract and engage site visitors—and the list goes on.

    Author: Conor Bond

    Source: Crayon

  • Predictive analytics in customer surveys: closing the gap between data and action

    Schermafbeelding 2018 01 24 om 10.02.51Customer surveys are a conduit to the voice of the customer (VoC). However, simply capturing survey data is no longer enough to achieve better results.

    When used appropriately, customer surveys can help companies more effectively identify new markets with the most potential for success, create a data-driven pricing strategy, and gauge customer satisfaction. However, capturing survey data is only the first step.

    Companies must analyze and act on survey data to achieve their goals. This is where predictive analytics comes into the picture. As illustrated in Figure 1, companies using predictive analytics to process survey data achieve far superior results across several key performance indicators (KPIs), compared to those without this technology. 

    Since happy customers are more likely to maintain or increase, their spend with a business, growth in customer lifetime value among predictive analytics users signals improvement in customer satisfaction rates. Similarly, companies using this technology also attain 4.6 times the annual increase in overall sales team attainment of quota, compared to non-users. This correlation indicates that predictive analytics can help companies convert survey data into top-line revenue growth.

    Use of predictive analytics to forecast and predict the likelihood of certain events, such as potential sales or changes in customer satisfaction, requires companies to have a comprehensive view of customer and operational data. Most organizations don’t struggle with a lack of survey data given the wealth of insights they glean through the activities noted above. Instead, they are challenged with putting this data to good use. Indeed, findings from Aberdeen’s May 2016 study, CEM Executive's Agenda 2016: Aligning the Business Around the Customer, show that only 15% of companies are fully satisfied with their ability to use survey data in customer experience programs.

    How to Use Predictive Analytics to Maximize Your Performance

    Data shows that Best-in-Class firms (see sidebar) are 20% more likely to be fully satisfied with their use of survey data when conducting customer conversations. A closer look at these organizations reveals that they have 59% greater adoption rate when it comes to predictive analytics, compared to All Others (35% vs. 22%).

    For any organization not currently using predictive analytics to analyze survey data, this technology holds the key to significant performance improvements. As such, we see that with a mere 35% adoption rate, many top performers could use predictive analytics to do even better.

    One mistake companies make when adopting new technologies is assuming that simply deploying the technology will result in sudden – and recurring – performance improvements. The

    situation is no different with predictive analytics. The fact of the matter is, if an organization is looking to increase customer lifetime value or profit margins, the organization must design and execute a well-crafted strategy for utilizing predictive analytics in conjunction with customer surveys.

    On a high level, predictive analytics can be used in two ways:

    1. Systematic analysis: Organizations can establish an analytics program to measure and manage survey data on a regular basis. These programs are aimed at accomplishing certain goals, such as gauging customer satisfaction levels at regular intervals to correlate changes in customer satisfaction rates with changes in the marketplace and overall business activities.

    2. Ad-hoc analysis: Companies can also analyze survey data on an as-needed basis. For example, a company could conduct a one-time analysis of the potential customer spend in a new market to decide whether to enter that market.

    It’s important to note that companies can use both systematic and ad-hoc analysis. Use of systematic analysis allows organizations to continuously monitor their progress towards ongoing performance goals, such as improving customer satisfaction. Ad- hoc analysis, on the other hand, allows companies to use the same analytical capabilities to answer specific questions that may arise.

    Having outlined the two general ways companies use predictive analytics, it’s also important to share the two general types of processes that can be used to produce such analysis:

    1. Statistical analysis: Predictive analytics can provide decision maker across the business with insights into hidden trends and correlations. For example, companies conducting statistical analysis can identify how use of certain customer interaction channels (e.g. web, email, or social media) correlates with customer satisfaction rates as revealed through surveys. This, in turn, allows companies to identify which channels work best in meeting (and exceeding) the needs of target clientele.

    2. Modeling: This second type breaks into two sub-categories:

    1. Forecasting: Companies can use historical and real- time survey data to forecast the likelihood of certain outcomes. For example, a company curious about the potential sales uplift to be expected from a new market would survey potential buyers in the area and ask about their intent to buy and preferred price-points. The forecasting capability of their predictive analytics platform would then allow the company to forecast potential sales numbers.

    2. Predicting: This analysis refers to analyzing historical and real-time survey data to estimate a specific result that might have already happened, might happen currently or will happen in the future. For example, an organization might decide to build a model that helps identify customer spend in a specific market. This might start by developing a model for past sales results where the model produces a result similar to the actual results observed by the company. Having ensured the accuracy of the model, the organization can now use it to predict current and future sales based on changes in the factors built into the same predictive model.

      The difference between forecasting and predicting is that the former only looks at future events or values whereas the latter can look at future, current or historical events when building models. Also, the former requires relying on already available past data (e.g. snow blower purchases) to make forecasts whereas the latter allows companies to predict a certain outcome, in this case snow blower purchases by looking at related factors influencing this result, including recent temperatures, change in average income, and others.



    Companies have many ways to capture survey data, however only 15% are fully satisfied in their ability to use this data. Predictive analytics helps companies alleviate this challenge by answering business questions designed to improve performance results.

    However, it’s imperative to remember that the statistical insights gleaned through predictive analytics, as well as the models predictive analytics can produce, will only yield results if companies act on the intelligence thus acquired. Don’t overlook the importance of coupling analysis and action. If you are planning to invest in this technology (or have already invested but seek to improve your results), we recommend that you make bridging the gap between data and action a key priority for your business. 

    Author: Omer Minkara

    Source: white paper Aberdeen Group (sponsored by IBM)

  • The four customer journey archetypes

    The four customer journey archetypes

    Most marketing experts agree that it’s not enough to give customers a satisfying initial experience with a product. Instead, product managers must offer them a compelling series of experiences—a customer journey—to keep them coming back for more. The design of customer journeys is the new marketing battleground.

    However, marketing experts have yet to develop a framework that can help managers with that design challenge. Too often they tell companies to routinize customer journeys—to make them as effortless and predictable as possible. Our research shows that this advice is overly simplistic. In fact, following it can sometimes backfire on a company.

    Though some journeys might require little effort (for example, watching movies on Netflix or reordering meals on Seamless), others demand considerable mental or physical exertion (learning a new language on Duolingo or working out on a Peloton bike). Customers value both kinds of experiences.

    Likewise, some journeys tend to be comfortingly familiar (like using Old Spice aftershave or grabbing lunch at Panera Bread), while others are unpredictable, surprising, and exciting (like meeting and chatting with other users of the dating app Bumble or playing World of Warcraft with friends). In many circumstances, customers actually relish the unexpected.

    Drawing on five years of research into customer experiences across a wide range of product categories and on feedback from workshops with marketing academics and executives, we have created a framework to help managers design compelling journeys that keep customers returning many times over. We call it the customer journey matrix. It includes four archetypes:

    • routine is effortless and predictable.
    • joyride is effortless and unpredictable.
    • trek is effortful and predictable.
    • An odyssey is effortful and unpredictable.

    None of the archetypes is universally superior to the others; all four can be used to keep customers returning frequently. They can be applied to a variety of physical and digital goods and services (all of which we refer to as “products”). Each kind of journey can unfold at any pace—daily, weekly, or monthly—and last for any duration of time, from a few weeks to several years.

    In this article we’ll first describe the four customer journey archetypes and their corresponding design principles, and then offer managers a guide to creating the ideal journey for their product.

    The Routine

    A routine is a simple procedure for completing a recurring task and typically involves a trigger for an activity that produces a reward. (For instance, the morning is a trigger to brush your teeth and be rewarded with fresh breath.) While all journeys follow patterns, routines are especially repetitive. They’re sometimes also called customer habits or rituals.

    Routines are well suited for utilitarian products that make tasks incrementally easier and more predictable. For example, ultrasonic toothbrushes increase the efficiency and effectiveness of customers’ oral care regimens. Mobile banking apps allow busy people to skip unnecessary trips to the bank. Quick-service chains give commuters an easy way to pick up food and beverages. In any routine, the less friction encountered, the more satisfied the customer is.

    Product managers can help customers build enduring routines using two design principles—streamlining the user experience and ensuring consistency across encounters. The goal of streamlining is to eliminate all non-value-added touchpoints, whereas the goal of ensuring consistency is to help customers learn the routine and perform it without much thought.

    Among quick-service chains, Starbucks has been especially relentless in streamlining its mobile ordering process, especially for grab-and-go customers at high-traffic locations. The Starbucks mobile app remembers customers’ preferred stores and payment methods, enables rapid reorders of favorite items, locates the nearest store and estimates the wait time, and shows where to pick up orders inside the store. The chain has even opened Starbucks Pickup stores that fill only mobile takeaway orders. And it has mastered consistency by creating standard protocols for preparing menu items. A caramel macchiato is made the same way in Los Angeles as it is in Omaha.

    Amazon leads online retailers in facilitating shopping routines. Conveniences such as one-click ordering and next-day delivery streamline its customers’ journeys. The site’s ordering process rarely changes—and only subtly when it does—minimizing the need for customers to relearn it.

    The Joyride

    Joyrides are amusing journeys that allow people to escape the tedium of everyday routines. Effortless, unpredictable, and a lot of fun, joyrides work well for products that deliver an on-demand thrill, such as music-streaming platforms, sports media, and video games. Joyrides can also be used in brick-and-mortar settings such as fast-fashion stores with high product turnover, local cinemas with weekly releases, restaurants with rotating menus, and bars with happy-hour specials.

    Just as it is for routines, streamlining is necessary for joyrides, though it isn’t enough to create them. Streamlining only mitigates pain points; it doesn’t induce pleasure. To facilitate joyrides, companies must also apply the design principle of endless variation across the customer journey to generate frequent moments of delight. In the game Candy Crush Saga, for example, players swap adjacent candies to create rows or columns of three matching candies. To make that activity fun, the game varies the candies, color schemes, sound effects, challenges, and constraints across nearly 10,000 levels.

    Many movie theaters facilitate joyrides by premiering a new film every week, but those of Alamo Drafthouse Cinema go a step further by frequently updating their menus. The company’s chefs also occasionally plan themed menus based on the movies shown (such as African cuisines for Black Panther).

    Consumer-generated content is another way to provide endless variation. On TikTok, new users are instantly immersed in a For You feed with trending videos they can swipe through. One video might feature a cat pouting while sad music plays; the next might show a cooking demonstration set to pop music. The staggering variety is part of the fun. Over time, users might like or comment on videos and discover creators they want to follow. TikTok’s algorithms constantly process the engagement data and use that information to customize the feed.

    The Trek

    Treks are predictable journeys in which customers labor to achieve challenging long-term goals such as learning a language, recovering from surgery, and saving for retirement. Typically associated with personal service providers such as tutors, coaches, and financial advisers, treks are now increasingly facilitated by mobile apps and smart products, including educational apps like Babbel; wearable devices that monitor health indicators, such as the Apple Watch; and financial-planning tools like Mint. Customers return frequently to products that enable treks because they need considerable support to make progress toward their goals.

    Companies often ease the work involved in treks with the design principle of goal-posting. Essentially, that involves breaking ambitious objectives into increasingly smaller ones until the next goal is so small that it spurs the customer to act. Rewards for hitting each target—which can be as simple as a few words of congratulation (“Good job!”) or changing colors from red to green on a tracking dashboard—are often added to motivate the customer.

    A product that excels at goal-posting is MyFitnessPal. One of the app’s core features is a food diary, which breaks a customer’s long-term objective (such as losing 20 pounds) into weekly, daily, and per-meal targets. Per-meal targets are further broken down by macronutrients (protein, fat, and carbohydrates), net calories, and other things that the customer might wish to track, such as sodium. The app streamlines the work of entering meals in the diary with tools such as a searchable library of foods and the ability to copy friends’ meal inputs when dining with others.

    The budgeting program You Need a Budget facilitates treks for customers with the relatively large and abstract objective of saving money. It encourages them to set concrete goals for major outlays, such as a home purchase, college tuition, and retirement, and break those goals down into smaller targets. The program also invites customers to set spending limits and debt repayment goals. All these goals can be scheduled in a variety of ways, including weekly, monthly, or according to specific dates. Immediate positive feedback from an intuitive interface encourages customers to keep making progress.

    Some marketing experts argue that high-effort journeys must be infused with exciting gamelike features to keep customers motivated. In other words, they advise product managers to convert treks into odysseys. This advice is worth considering, but not all customers love the bells and whistles of gamified services. A trek with a well-defined series of achievable goals and affirming rewards can be just as motivating as an odyssey.

    The Odyssey

    If routines are the most ordinary type of customer journey, odysseys are the most extraordinary. Odysseys are challenging, thrilling, and unpredictable adventures that are fueled by a customer’s enthusiasm, determination, and sense of purpose. They tend to require great effort and generate a lot of excitement. While customers follow many routines in their lives, they usually have only a handful of odysseys at any given time.

    Odysseys are perfect for products that facilitate passion projects that customers are already highly motivated to pursue, such as cultivating a social media following, playing a strategy game, learning a performance art, filming a documentary, and training for a fitness contest. They keep customers returning to a product because they want to learn and grow. Unlike treks, odysseys don’t need a set end point; as outdoor enthusiasts often say, the journey is the destination.

    Odysseys are particularly common in the recreation industry. A key design principle here is substantive variation, which involves offering a diverse mix of customer thrills and challenges for functional reasons. Take CrossFit. In a typical session, coaches lead athletes through warm-ups, skill development, and high-intensity workouts that incorporate aerobic, calisthenic, and weight-lifting exercises. No two workouts are the same. Another key design principle for odysseys is journey tracking. CrossFit athletes closely track their own progress, but there’s no defined end goal. The journey is effortful, unpredictable, and seemingly never-ending—a true odyssey.

    Odysseys are also common in creative fields. Consider the intensive journeys facilitated by Adobe Creative Cloud’s portfolio of design, photography, video, and web-editing apps, or by the Juilliard School’s performance arts programs, which help actors, dancers, and musicians reach their potential. What Adobe Creative Cloud and Juilliard have in common is that they facilitate personal and professional development. (For more on the strategy of marketing personal transformation, see “The ‘New You’ Business,” HBR, January–February 2022.) Elements such as passion and purpose lend odysseys a unique sense of transcendence above the relatively ordinary experiences of routines, joyrides, and treks.

    Designing an Ideal Customer Journey

    A five-step process can help you craft the right kind of journey for your product and customers.

    1. Identify the best archetype for your product.

    Is it relatively effortless or effortful to use? Is the experience predictable or unpredictable? The answers to those simple questions reveal whether a routine, a joyride, a trek, or an odyssey will be most appropriate.

    2. Put the archetype’s design principles into action.

    If, say, your product’s archetype is a routine, strive to deliver a predictably satisfying experience by ensuring consistent touchpoints in familiar sequences. Marriott’s standardized check-in and check-out processes, for instance, make stays at its hotels easy for travelers, even in a new context such as a visit to a foreign city.

    If your archetype is a joyride, generate endlessly varied moments of delight, perhaps with in-house teams of content producers or machine-learning algorithms, or by crowdsourcing content from consumers (as Instagram’s feeds do).

    To create the goal-posting that a trek demands, partition the customer’s long-term objective into a series of much shorter term goals and reinforce the customer for achieving every small target. Fitbit, for instance, reminds users to take walks throughout the day and rewards them with badges, check marks, or progress icons when they do.

    For the journey tracking and substantive variation that an odyssey requires, you might set up a performance dashboard and offer a diversity of individual and communal activities that collectively advance the customer’s goal.

    3. Cue purchase decisions at the right time.

    The best time to invite these largely depends on the predictability of the journey. With routines and treks, which have knowable outcomes, customers are generally motivated to sift through pricing details at the outset. Once customers have developed a routine or embarked on a trek, however, they usually don’t want to be bothered with those details again.

    For joyrides and odysseys, which have unknowable outcomes, customers generally aren’t motivated to make big decisions at the start. Instead, they’re eager to get a taste of excitement as soon as possible. Only later, once they’ve become more involved in the journey, are they willing to invest in a major purchase or subscription. You need to give them ample time to use the product before asking them to make cognitively demanding and financially significant decisions. If providing free services at the beginning of the journey is too costly, consider offering a cheap starter option.

    4. Streamline the journey at every opportunity.

    This is the design principle that applies to all four archetypes. To keep their brands competitive, product managers must continually find new ways to eliminate non-value-added touchpoints from the customer experience.

    To facilitate routines, for instance, PayPal lists customers’ frequently used contacts on the landing page so that payments can be sent to those people within seconds. Customers just tap on a contact’s name, input the payment amount, review the transaction, and hit “send.” Customer routines should be so obvious that they require almost no thought or effort.

    Companies that provide other types of journeys have found new ways to streamline as well. Singapore Airlines’ in-flight entertainment system, which offers joyrides, recalls where passengers stopped watching movies on prior flights, so they don’t have to fast-forward to where they left off. To simplify its treks, MyFitnessPal offers a barcode scanner feature that customers can use with packaged grocery items to quickly log their calories and macronutrients. And to help streamline their customers’ odysseys, some Equinox gyms allow members to order a post-workout smoothie at the front desk on their way in so that they can avoid a wait afterward.

    5. Consider different journey archetypes for different customer segments.

    We’re often asked whether a single product can facilitate multiple types of customer journeys. The answer is a definite yes. In fact, many leading brands provide two or more journey archetypes in parallel.

    Tinder, one of the world’s most popular dating apps, facilitates different types of journeys for casual and power users. Some casual users are interested only in swiping through other users’ profiles and occasionally chatting with a match; their journeys are joyrides. In contrast, power users not only swipe through profiles but also message matches, juggle multiple conversations, meet potential mates, and then continue or end those connections after good or bad dates. Their journeys are odysseys.

    We’ve also observed joyrides among casual users and odysseys among power users at Pokémon Go, the mobile augmented-reality game. The aim of the game is to catch virtual creatures called Pokémon that randomly spawn throughout the electronically mapped world. For casual players the game is an occasional joyride during walks or work commutes. For passionate gamers, however, it’s an odyssey that can consume much of their leisure time. People in the latter group band together for in-game battles and go to great lengths to find rare Pokémon.

    Meanwhile, Amazon facilitates both treks and routines. Before purchasing high-ticket durable items like microwaves, sofa beds, and televisions, customers often sort through pricing information, ratings, and detailed reviews to make informed decisions. One could interpret those laborious experiences as treks. However, in consumable, low-ticket product categories, such as groceries and household supplies, Amazon encourages rapid repurchases via a buy-again feature and automated routines using its subscribe-and-save feature.

    When companies have customers enrolled in multiple types of journeys, they’re more likely to retain them. As some journeys lose their allure, others might begin to gain momentum. The net effect is that customers are continually engaged with the company’s products on one journey or another.

    To succeed in today’s hypercompetitive market, products must facilitate compelling customer journeys. But there’s no one right way to design them. The customer journey matrix offers product managers four proven archetypes to choose from—routines, joyrides, treks, and odysseys. Each of these archetypes and its design principles can help companies keep their customers returning again and again.

    Authors: Ahir Gopaldas & Anton Siebert

    Source: Harvard Business Review

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