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November 4, 2019

How To Have A Personal Touch In A Digital Ecosystem

The world is more connected than it was five years ago -- and exponentially so compared to the five years before that. But as we adopt auto-reply systems, customer service bots and even let our phones screen our calls, it seems this hyper-connected world has resulted in less human-to-human interaction.

Because of this, brands run the risk of losing that personal touch -- and ultimately their opportunity to differentiate on service. Of course, it's table stakes that the core product needs to be competitive, but how can brands set themselves apart when there may be little or no direct interaction with their customers?

1. THE DIGITAL EXPERIENCE MAY BE YOUR ONLY DIRECT CONNECTION TO YOUR CUSTOMER.

So, take the time to get it right. A frustrating digital experience results in an unhappy customer who can easily find your competition from the same browser window or app store. According to Formstack, 57% of internet users say that they won't recommend a business with a poorly designed mobile website.

2. BE TRANSPARENT, AND PUT USEFUL INFORMATION IN THE HANDS OF YOUR CUSTOMERS.

Let your customers know that there are real people behind your product; this transparency lets people appreciate the amount of work that went into making the experience. The Domino’s Pizza Tracker is a great example, but this concept can be applied across virtually any industry. Fulfillment centers could show the origin and history of their product, as well as the process of boxes being packed and loaded for shipment. Wouldn’t it be amazing if your doctor’s office actually let you know when they are running late and why?

3. TAKE CARE OF YOUR PRODUCT EVERY STEP OF THE WAY.

If a customer purchases a sweater in a store, the salesperson wraps it in tissue, folds it nicely and puts it in a branded shopping bag. If a customer orders that same sweater online, it arrives in a plastic bag inside a box. This experience may make customers feel less cared for, at least compared to an in-store purchase. Experience matters, even if you aren't personally interacting with your customer. Look out for small ways you can optimize your experience both in-person and online.

4. GO ABOVE AND BEYOND.

Rideshare drivers who deliver you quietly and safely to your destination get solid reviews, while those who stand out often offer passengers water or engage them in avid conversation. If a customer orders food to be delivered from your restaurant, why not include a little something extra that might incentivize them to order from your restaurant again next time? Even a magnet, a cookie or a handwritten note might be the personal touch that makes a lasting memory. According to Accenture, companies that excel in customer experience enjoy a 3% to 7% revenue lift, which can have a huge impact on your bottom line.

5. EVERY PERSONAL INTERACTION MEANS WAY MORE THAN IT EVER HAS IN THE PAST.

In a hotel, you might opt for a digital key and quite literally not interact with any hotel staff during your stay. But what if the concierge greeted you by name, or what if the bartender knew that you like two olives in your martini? According to a PwC study (reported on by Multichannel), 74% of respondents said "they wanted more human interaction, not less. And 64% of respondents said they felt companies have lost touch with the human element of the customer experience." Companies can do this by collecting and aggregating data from all customer touch points into a customer data platform and using technologies such as AI and machine learning to gather insights so that they can truly know and personalize service for each customer.

Brands need to be intentional about how they are interacting with customers in order to make the most of each and every interaction and differentiate themselves against the competition. Where will you start?

This piece was originally published at Forbes.com.

January 22, 2019

The Tech Behind a Digital Transformation

Digital transformation has become a hot topic as of late. Once you decide that your business needs one, how do you go about actually implementing the technology to bring your business forward? Here are three key ways that most businesses need to adapt for the digital age, and some technology that can help get you there:

ANALYTICS

Understanding how your business (and your market) is changing is critical. Where your users come from, what they want and what they’re doing is essential data you should be collecting. But collection is not enough -- your data needs to be aggregated, analyzable and accessible by those who need it.

Services like Google Analytics or Adobe Analytics can get you started on tracking user activity. Tools like mParticle can let you route your analytic events to multiple destinations, so if some analytics are better utilized by certain tools, you don’t have to integrate multiple analytics software development kits (SDKs).

Other analysis tools like Amplitude can help you take a step back from the actual data and see activity at a higher level. (Full disclosure: mParticle and Amplitude are both Bottle Rocket partners.) Are users having trouble finding where to start, or do they get lost in the middle of the process? We optimize for what we measure, so measure the areas you want to transform.

Once you have your analytics in place, you’ll want to create dashboards that can bring the most critical information to the forefront, so you can keep a spotlight on the most important things. Will it be higher user acquisition, larger purchases or shorter times to complete tasks? Building a baseline before you make changes will provide better insight into where you’re seeing the most benefit and will help justify the huge amount of work in the next two areas. There are many tools that fit this need, such as Tableau, Microsoft Power BI or Google Data Studio.

API’S

Another huge area of digital transformation is making your data more readily available to your own employees, partners or the general public. You’ll need to put a lot of thought into the API design, and tools like Apiary can make it easier to share and communicate your ideas to others. This doesn’t mean all your data should be public (far from it), but you should be thinking about how easy your data is to access and analyze.

Having a decade’s worth of invoices is great, but if they are stored on tape drive backups and can’t be retrieved easily, they are useless to everyone but the auditors. The infrastructure to convert your data into something that allows for APIs could be as big of a transformation as anything else you do. You might convert your data to an Amazon Web Services (AWS) data lake or have your APIs running on Google Cloud Platform (GCP).

Consider how your APIs will scale. Using cloud services such as AWS or GCP can help ensure you’ll have the ability to scale when you need it, but tools like Metrics can give you analytics on your APIs to make sure they are constantly available. Part of a digital transformation is being online 24/7, and poor performance can lead to stunted growth. Understanding which parts of your infrastructure will be affected first will let you plan and prioritize accordingly.

MOBILE STRATEGY

No matter what business you’re in, there will be some sort of mobile aspect to it. Whether it is customers ordering your products or services or keeping your own employees up to date with the latest information, people expect to be able to access anything, anywhere, right now. This doesn’t mean you must build a native mobile app for Android and iOS. Mobile websites and progressive web apps are becoming more and more capable and increasingly offer the functionality required for your digital transformation.

When deciding between various platforms, understand what your primary use cases will benefit from. Do you need precise location tracking with push notifications and hardware-level encryption? Then native apps are probably the way to go. Hourly access to send status updates and verify task completion? A svelte web experience may provide the most bang for the buck.

The value of your mobile strategy arrives when you’re able to use your analytics and APIs to connect with your users more dynamically. Using your analytics data to send the right messages to the right people at the right time can transform their experience with your brand. Extending functionality through your APIs that clients want or need can cement their loyalty for life.

BEYOND THE BASICS

Once these three big areas are in place, you’ll want to start thinking about reducing or removing as many manual steps in the process as possible. Will you automate your build systems to support continuous integration using tools such as Jenkins, or maybe automate testing? Automated testing can help ensure that any changes to your new digital ecosystem will continue working for your existing users.

A digital transformation is no small task and can take years to accomplish. Starting with analytics, APIs and a solid mobile strategy can help you build a road map that will propel your business to the next level.

This piece was originally published at Forbes.com.

October 25, 2018

The Five-Pointed Star of Mobile Payments

“Mobile payment” is a term that encompasses a lot of interconnected technologies, and you can’t really benefit from only doing one of them. You don’t necessarily need to build out all of these, but if you only build one, you may be setting yourself up for failure. Let’s break down each of the main aspects of mobile payments.

STORED PAYMENT INFO

By having the payment method linked and validated, the user can show a barcode at checkout, and it can save a lot of time if your usual customers make payments more than once a week. Anyone who can purchase faster in person means that you can handle more people with the same staff. Combined with mobile ordering, that stored payment becomes a one-tap option to pay, and you’ve totally removed the person from waiting in line. Users can be a little wary of giving their payment information away, so there has to be a good value proposition. Shortening their checkout is good, but making mobile ordering quicker is even better.

STORED VALUE

Storing value is when someone puts an amount of money into a system and draws it out slowly. Imagine it as a virtual gift card that is available through an app or website. This saves money for the business by lowering the total number of credit card transactions, and it can also help customers budget. If they only want to spend $50 per month on coffee, they can load just that much on their account and monitor it easily. If you add some loyalty perks, they may be able to stretch their dollar and visit a little more often.

It’s also possible to give them a little bit of extra value when they store it -- say, a 5% bonus on every dollar they add. If you allow loading value from bank accounts or other alternative payment methods, you can save even more in processing fees, which drops straight to the bottom line. If customers make a lot of small-dollar purchases (i.e., under $10), this can translate to large savings.

LOYALTY

Reaping the rewards from being loyal to a brand makes people feel valued. They’re more likely to visit or at least will consider your brand a little bit more than the alternatives since they feel like they’ll get something back in return. Using discounts to entice them also keeps your brand top of mind.

Gamification works as well. Customers like working toward a goal because it gives them a sense of accomplishment. Exclusive rewards for mobile orders can encourage users to go even deeper into your mobile payment ecosystem and get them to try a new behavior they might otherwise skip. Customizing the payment experience based on your customer is easier since the experience is on their own device, so special offers and exclusive rewards are easy to show them without making other customers feel left out. Customers who see your brand as part of their identity are more likely to value these loyalty rewards.

MOBILE ORDERING

Saving a few seconds by not swiping a card is great, but saving the minutes in line is an even bigger return for the customer. Mobile Orders mean that patrons are thinking about your brand away from your location, which is a great sign that they’re a loyal supporter. Since their payment info is stored safely with you, they can order even if they forgot their wallet or don’t have it handy in that last meeting of the day. If you don’t want to store payment info, you can always use the mobile device’s payment options (Apple Pay or Google Pay), which provide security and peace of mind for the user.

Younger and more time-limited customer bases seem to really be embracing mobile ordering, so this may need to be a priority for companies that appeal to those demographics. Mobile ordering continues to expand, but in doing so, it becomes less of a differentiator. Multiple points on the star have to be executed well to provide real value to the end user.

ALTERNATIVE PAYMENT METHODS

Integrating other payment methods such as Paypal, Venmo or even Bitcoin could provide the push that some people need to go with mobile payments. Even different card vendors can provide methods to make their payment information easier and safer to retrieve. When you combine this with stored value, you can transfer and verify all the funds separately from the purchases so customers don’t get frustrated during the purchase process and go somewhere else. Unbanked or other underserved groups are currently an untapped market; the early movers in this space could take an early market share lead.

When considering building a mobile payment solution, be clear about what your needs are and what your customers will value. Often, it’s not a single feature that they care about but the combination of several. Each additional feature requires additional work, but the whole solution is worth more than the sum of its parts.

This piece was originally published at Forbes.com.

May 25, 2018

Three Top Tips for Your Analytics

This piece originally published at Forbes.com.

User analytics are critical to understanding the success of your solutions and where they can be improved. Not all analytics are the same, and what you measure for one product may not apply to your others. Let us consider a few ways to make analytics work for your needs.

TRACK THE RIGHT INFORMATION

It’s common to think that pageviews or time-in-product are the most relevant stats to track, and while they are a good baseline, they are not the sole measure of success. Conversions are probably more important, as it's critical to know whether the value proposition you make is being received by your users or customers. This could be downloads based on viewing the app listing, sign-ups for your service after seeing a splash screen or if add-on products and services are being selected.

It is also important to look at how long your users have been a part of your service. A new user might have different preferences than a long-time user, so you may want to present different options at first. For example, the first time someone uses an app to order food, offer the most popular items right away and let them have a quick success. When they return, they might be more interested in exploring the entire menu since they enjoyed what you offered them the first time. By also tracking which users are most active, you’re finding your biggest supporters and the ones who will provide the biggest ROI. You’ll want to keep an eye on these users to see if you notice any trends or new behaviors.

BECOME A MASTER OF INTERPRETATION

When you’re looking at your analytics, you have to be careful to interpret the results properly. Some stats are easy, such as monthly active users, where higher is always better. The total time spent on your service or the number of page views can be good, too, especially if your product is ad-supported or correlates heavily with customer satisfaction.

However, more time spent ordering could mean that users are confused by the interface and less likely to return. Sometimes you want users to complete tasks more quickly, which could look like a problem if you only look at total time in your product. Now, if users who spend a long time ordering also order more (a correlation I’ve seen in some apps we’ve worked on), you’ve found an optimized solution.

It's also important to not look at your analytics in a bubble. Are the support channels on your website being used more than last year? This could be an indication of a problem getting worse and people needing to contact support more. But it could also be that more users are finding success with online support over their traditional phone support options.

If phone calls have dropped significantly, maybe you’re seeing a net improvement and are able to handle your support needs more efficiently. As new communication channels open up through mobile, voice, chatbots and social media, existing solutions may see significant drops. Very few people mail letters to express their feedback anymore, even though this used to be common!

USE YOUR METRICS CORRECTLY

Now that you’re tracking the right moments and interpreting the data properly, what do you do with the information you’ve gathered? In general, you want to make the actions that users enjoy easier to find and quicker to accomplish. Are there rarely used parts of the experience that could be removed? If there isn’t enough ROI for some features, it’s probably worth removing them in the long run. For example, some loyalty and ordering apps also include mini-games under the guise of being an entertainment option for kids. However, these features are almost never used over other forms of entertainment on the device and not worth the investment to keep updating them to support new OS and hardware revisions.

Conversely, you need to also look at where users are spending their time and lean into making the experience as satisfying as possible. Do your customers like exploring all the different options? If you have an e-commerce site and show three related products on your product pages but your analytics show that a lot of customers explore these options, perhaps you should try showing four or five. Another consideration is how the platform might affect the experience. Do desktop users perform more complex actions, whereas mobile users are more focused on simple tasks? Tailoring the experience to each user could have huge returns on satisfaction.

In the end, business goals have to be reconciled with user desires. Analytics measure what users are doing, but the interpretations and actions taken have to be thoughtfully considered. If the business goals can be distilled to their core enough, like “increase orders,” it’s easier to put the right lens on the data and take actions that help drive the right behavior or remove parts of the experience that cause friction. Consider all your options, but make decisions based on your data.

January 9, 2018

What you need to know about AI

This piece was originally published at Forbes.com.

Lately, when clients come to me as a consultant, Artificial Intelligence (AI) usually comes up in our conversation. And when I’m asked, “How do I use it?” that tends to actually mean “What is it?” Let’s reach a basic understanding of AI so when you’re ready to explore what AI can offer, your discussion can be as productive as it can be.

WHAT IS ARTIFICIAL INTELLIGENCE?

As the name implies, AI is the intelligent behavior of machines. Most companies could utilize AI to interpret complex data. Here’s how it works (in a very simple way): The AI model asks a set of data a question and returns an answer. To accomplish this task, an AI model needs to understand the data it’s interpreting. So, for AI to deliver accurate, useful information, an AI model needs to be trained on the data it’s given. We’ll get into that soon, but first let’s talk about that data.

LEARNING FROM DATA

For AI to work, it needs to learn from specific kinds of data. With organized, not random, data, an AI platform can learn what it needs to. Let’s say you want to train an AI model to identify dogs in images. Organized data would consist of animal images, including dogs, to help the AI discern what is and what is not a dog. Random data (in this case, images of tables, lawnmowers, anything not reasonably close to our concept of a dog) doesn’t help the AI distinguish dogs from other animals. Know what’s in your data and you should be able to avoid any randomness.

At this point, I should clarify that AI isn’t actually telling you what something is — AI tells you what something probably is not. This is determined through a prediction percentage -- you’re not teaching an AI model to know an animal is a dog but rather training it to tell you it’s a certain percentage confident it recognized a dog. If you’ve been feeding your AI model with images of only dogs and cats, then introduce an image of a squirrel, your AI will be less certain of what it sees. But, once you teach the AI model what a squirrel looks like, the AI can discern with more certainty.

HOW TO TRAIN YOUR AI

Machine learning, the ability for computers to learn without being programmed, can take place a couple different ways. One way is supervised learning, where an AI model infers a function from labeled training data. Those images of animals I mentioned earlier would be labeled “dog,” “cat,” "hippopotamus,” etc. to help the AI learn. The other machine learning method is unsupervised learning. This is where machine learning draws inferences from data sets consisting of input data without labeled responses — you provide a bunch of pictures of animals with no descriptions and let the AI figure out what is and what is not a dog. Remember to, with either approach, provide organized data that your AI will learn from.

Google provides a lot of data sets and pre-trained AI models for purchase. But, they’re all about object recognition and will only do a good job of recognizing things that existed when the model was trained. So, a Google AI model may have learned what a bike and pogo stick are at some point, but a newer invention, like a Segway, could confuse it.

BEYOND CATS AND DOGS

I’ve led or been on some teams that have worked on training data for tasks other than image recognition, like classifying audio samples or, during an innovation session, recognizing what restaurant is delivering food by identifying food service workers and recognizing what was being delivered. The latter is an excellent example of what can happen when you train very specific models. In this application, the AI model learned from uniforms, not beverage cups, cars or even people. The data set provided in this case included shapes of what delivery drivers could be carrying and the clothes they wore.

The accuracy of your AI model is really about the bucket of data you give it. You need a lot of pictures, and they need to be of a similar quality. The more similar they are, the less training you likely need.

WHAT COULD GO WRONG?

Okay, our hypothetical AI is up and running. What is at stake if it’s wrong? Within your own organization, determine the impact of a false positive or false negative. AI that determines what is and isn’t email spam could afford to let some spam through but could create problems if it marks something important as spam. Imagine the consequences of AI providing results of x-rays with a false negative cancer diagnosis.

Now, if you feel more comfortable with how AI works, you can begin the challenging task of figuring out where it fits in your organization.

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