Omni-Channel Retailers Achilles Heel: Shipping Costs?

Posted on Posted in E-Commerce

Why does Amazon push its consumers to get Prime when they take a loss in shipping costs?

  • Unlike brick and mortar retailers, Amazon is an online first commerce platform, and aims to reduce any friction that customers might have in purchasing online. Predictive analytics research persistently shows that a large number of customers abandon a shopping session when fast and free shipping is not available.
  • Promoting Prime and taking a loss on shipping costs are not necessarily correlated though even if retail data analytics might have lead Amazon to couple them. Amazon has strategically chosen Prime as a loyalty program, with the intent of increasing it’s business moat over time. Customers love Prime because of all the fun perks, including fast and free shipping they receive. Amazon in turn retains a loyal customer.
  • There are competitive advantages in offering fast and free shipping although a retailer takes a loss on shipping costs. Online commerce continues to take share from brick and mortar (physical stores). In 2018, online commerce accounted for 10% of total US Retail Sales. That figure is expected to go to mid teens or higher by 2021.
  • Amazon can afford to offer fast and free shipping since they have other businesses – AWS, Marketplace and Advertising – that compensate for the margins lost in providing free shipping.
  • Brick and mortar retail businesses on the other hand either lose business to online competitors or end up impacting margin when customers purchase product from their online commerce platform instead of their physical store.
  • Since they usually do not have other high margin businesses to fall back on, retail stores not investing in predictive analytics are competitively weakened by this shift online coupled with the margin impacting free shipping offers.
  • Smart retailers, Amazon or some omni-channel retailers are continuously investing and partnering with consumer data analytics and predictive analytics expertise to consistently reduce the cost of shipping and time to doorstep.
  • A recent case study we did for an omni-channel retailer touches upon how consumer data analytics and it’s predictive analytics capabilities have been leveraged to cost effectively offer what customers love – fast and free shipping.
  • Fast and free shipping is here to stay. Smart retailers understand that it is important to provide what the customer expects. They compensate the impact of that by investing in retail data analytics and supply chain and fulfillment optimizations to reduce costs and time.

Microsoft Draft Helps Developers Adopt Kubernetes

Posted on Posted in DevOps, Technology

Microsoft’s Deis releases Draft that makes it easy for developers to build applications that run on Kubernetes. Draft does this by providing tools and simplifying steps required to build for Kubernetes. If your enterprise has looked at containerization, docker, kubernetes before and looked and looked, this latest tool might very well nudge you to take the dive!

As Draft’s github account indicates, it targets the “inner loop” of a typical developer workflow: right when they are building an app and hacking code but before code is committed to a version control repository. At this time, applications written in six languages – Python (Newstar’s favorite language), Java, Go, Node.js, Ruby, PHP- are supported.

Using Draft is a simple 3 step process fitting right into that developer “inner loop” we spoke before:

  1. draft create to containerize your application based on Draft packs
  2. draft up to deploy your application to a Kubernetes dev sandbox, accessible via a public URL
  3. Use a local editor to modify the application, with changes deployed to Kubernetes in seconds

Running the draft create command will result in Draft creating a dockerfile and and Kubernetes Helm chart for that app.

Here is how it would look for an example Python app which uses Flask for an “Hello World” server:


$ draft create
--> Python app detected
--> Ready to sail
$ ls
Dockerfile app.py chart/ draft.toml requirements.txt

The draft.toml file contains basic configuration information about the application. See the Draft User Guide for further information and available configuration options on draft.toml.

Next would be invoking draft up to deploy the app to a Kubernetes cluster.

$ draft up
--> Building Dockerfile
Step 1 : FROM python:onbuild
onbuild: Pulling from library/python
...
Successfully built 38f35b50162c
--> Pushing docker.io/microsoft/tufted-lamb:5a3c633ae76c9bdb81b55f5d4a783398bf00658e
The push refers to a repository [docker.io/microsoft/tufted-lamb] ...
5a3c633ae76c9bdb81b55f5d4a783398bf00658e: digest: sha256:9d9e9fdb8ee3139dd77a110fa2d2b87573c3ff5ec9c045db6009009d1c9ebf5b size: 16384
--> Deploying to Kubernetes
Release "tufted-lamb" does not exist. Installing it now.
--> Status: DEPLOYED
--> Notes:

http://tufted-lamb.example.com to access your application

Watching local files for changes...

 

Once successfully deployed, interact with your app to make sure it all works right!

Keep in mind that Draft is experimental at this time but is shaping up to be a useful tool for those who desire to take a dive into the world of containers and Kubernetes but so far did not know how!

Retail’s Intel Moment Or Why Omnichannel As We Know It Is Dead

Posted on Posted in Technology

Retail Omnichannel As We Know It Is Dead

Retail’s Quandary

First it was the print media. Now it is retail. Software may not be eating the world just yet but it certainly is painfully transforming sectors. Nary a day goes by when we don’t hear a retailer struggling to meet its sales targets yet again. Store sales languishing, ecommerce growing albeit at lower margins, and Amazon’s dominance looming ever so larger. The industry has certainly seen this coming for sometime. And there have been numerous attempts to respond, the most noticeable one being Omnichannel. Yet brick and mortar retailer after another have been reporting dismal numbers and these initiatives have not been making the expected dent.

Perhaps it is time to take a pause. Think long term and more strategic as opposed to the current tactical responses being dished out under Omnichannel.

Perhaps it is time to look at other’s who have been in a similar situation before. In an industry that is inflicting the pain today but was struggling then. Technology and the story of Intel.

Intel’s Reinvention Story

While Intel created the first microprocessor in 1971, it was also an early developer of RAM memory chips and it constituted a large portion of the overall business until the 80’s. The early 80’s saw rising competition from Japanese memory chip manufacturers and resultant decrease in profitability. In a move documented in multiple business books, Andy Grove and Gordon Moore sat down and asked themselves:

if we were fired and asked to leave, what would the new leadership at Intel do?

They then very objectively came up with a plan that included focusing exclusively on microprocessors and getting rid of the memory business. As Andy Grove later wrote, they then decided to:

“walk out of the door, come back and do it ourselves”

The rest as they say is history.

What Does That Have To Do With Retail?

We will get there in a moment. But first some history. Traditional retailers early response to Amazon and ecommerce was to set up a separate ecommerce unit completely divested from its traditional brick and mortar business. To borrow from biology, akin to an appendix or vestigial organ as opposed to one that was at the center of its future business. With every passing year, ecommerce and store businesses kept growing to meet growing demand. As the competitive threat of ecommerce started to loom large, retailers with dual presence have responded by devising OMNIchannel as their strategic advantage. Multiple fulfillment and delivery models such as “Buy Online Pickup In Store”, “Ship From Store” etc, have been launched with the belief that customers wanted that. When in fact what they have always wanted is a great product at a compelling price point, when they want it. All without making them think!

Meanwhile, internally, ecommerce and brick and mortar businesses continue to operate separately for the most part and in fact are competing for the same customer. Two businesses, two cost structures, two technology stacks, attempting to talk to one another under the guise of Omnichannel and working to satisfy the same customer.

Retail’s Rallying Motto

More can be done to reposition the store as the tip of the digital ecommerce iceberg.

It’s time for retail to borrow from Intel’s playbook and take a stance. Ask what Andy Grove and Gordon Moore asked themselves:

if we were fired and asked to leave, what would the new retail leadership do?

Then do what they did. Walk out the door, come back and just do it.

Still unsure and need to kickstart that thought process? Ask yourselves and your associates this simple question:

What if the web came before physical stores?

Yes. You got that right. What if your ecommerce platform already existed and was thriving before you opened your first store? How would you then repurpose your business? Operate two of everything to serve a single customer? Or you would put all your eggs in one basket and take a stance?

The implications of this question are far reaching and we’ll talk about them in another article. What brands will survive, which categories could build a semblance of a moat, how technology should be leveraged and associates organized. All along retailers have attempted to bring technology into retail. They should work the other way around instead.

Meanwhile, it’s survival time. Choose wisely.

Conclusion

If there is anything that the print media’s transformation from early 2000’s and Intel’s strategic shift from 1970’s tells us is that who drives the change matters. While transformation is painful up close, who drives the change determines how deep and how long that pain lasts. And in what shape one emerges at the other end.

It’s Retail’s turn to choose.

ChatBots Or Not: Craze Du Jour Or Something More?

Posted on Posted in Technology

Lately Chatbots have been the talk of the town. Whether it is the infamy of Microsoft’s Taye chatbot or the announcements of chatbot API’s and apps from Facebook at F8 and Kik, they appear to be dominating the conversation, if not contributing to them. This raises interesting possibilities for Online Retailers and Digital E-Commerce Platforms as they evaluate opportunities and investments in the conversational commerce space. E-Commerce marketing and product development organizations can formulate a winning strategy by looking at key market trends, learning from investments in mobile apps and identifying compelling areas that can provide a renewed growth impetus to their ecommerce ecosystem.

Messaging Apps MAU Surpass Social Networks

messaging apps growth and e-commerce

A recent report by eMarketer points to the massive growth and proliferation of messaging apps. Not only has the monthly active user count of the top 4 messaging apps exceeded those of top 4 social apps, but on numerous other factors like engagement rates and retention they continue to demonstrate strength. Between Whatsapp, Facebook Messenger, WeChat and Viber, the top 4 messaging apps, there are over 3 billion active users globally. Other chat apps like Kik, Line and Snapchat command upwards of 200 million users.

While chat apps boom in the US, elsewhere these apps have gone beyond messaging and offer various e-commerce capabilities including booking tickets, flight check-ins, requesting cabs, and purchasing goods all without leaving the messaging app itself. The rise of conversational commerce and chatbots, supplements the need for mobile apps or sites and engages customers where they prefer to be and an interface that requires no learning.

Shifting Trends In E-Commerce Referral Channels
e-commerce referral channels

While organic, paid and email continue to be the dominant traffic drivers in 2015, social and messaging apps have begun to make a noticeable uptick as referral channels.

Email marketing in particular is showing signs of flagging. Customers are growing weary of the traditional bulk emails from multiple marketers that show up in their inbox first thing in the morning. Not only do these emails miss the mark in terms of timing, they also tend to lack in critical elements of deep personalization and intent. Organic search on the other hand presents it’s own set of challenges for newcomers striving to dislodge the Google SERP rankings.

This is one area that is ripe for change and messaging apps as well as chatbots are likely to emerge as the referral channel that takes away share from the existing main traffic drivers.

Mobile Garners Largest Share Of Traffic

Share_of_App_Time_Spent_by_Rank_Chart_reference

A quick review of total engagement and share of app time spent continues to demonstrate mobile garnering the majority share of shopper traffic and the top 5 apps cornering over 90% of that time. Not only are the remaining apps relegated to infrequent usage, a full 25% of downloaded apps are used only once and then abandoned!

By mid-2015, Americans on average had spent approximately 68 hours per month on their mobile devices. That number rises even further to more than 90 hours per month among millennials.

E-Commerce product development organizations should consider these statistics as they decide on how best to invest in messaging apps and chatbots to grow their e-commerce ecosystem.

3 Ways To Leverage These Dominant Trends And Chatbots

Better Customer Engagement

Retailers have the opportunity to converse with customers where they desire and demonstrate maximum intent to engage and complete their transactions. Instead of one size fits all email blasts that continually indicate decreasing open and click through rates, by tailoring interactions based on customer and demographic preferences, better convertible traffic can ensue. Varying these across messaging, social or email based on big data analytics, sentiment analysis and other signals, allows for fruitful customer engagements overall.

Explore New Revenue Streams

As e-commerce businesses look to attract millennials and look to increase revenue from younger demographics, messaging provides an excellent extension to their e-commerce platform. Secondly, mature platforms now have the ability to extend their reach far beyond site and instead conduct various forms of commerce transactions that would not be readily possible or costly via traditional site development.

Proactive Customer Service

While site chat has been around for a while now, messaging apps allow customers to engage via an interface of choice and enables the scale that comes from automation of most frequent customer service calls. When is the item going to be shipped, what is the tracking number, what are available discounts, price match commerce transactions are some of the few ways in which customer service can be taken to a new level and can be a revenue generator too.

While we are in the initial stages of chatbot technology adoption and e-commerce enablement via messaging apps, Retailers and E-Commerce Platforms have the opportunity to make the appropriate strategic bets, that will both protect and grow their brands and customer bases.

Is your organization considering investments in messaging apps and chatbot technology? Would love to hear how you are planning to stay ahead of the curve, stay relevant across your customer base, and optimize your e-commerce platform and ecosystem.

How Not Managing Mobile Customer Feedback Makes You A Rookie!

Posted on Posted in Technology

This article first appeared on devops.com.

Managing mobile customer feedback effectively could be the single most important success factor for your company and customers. Call it addiction or habit, but every passing day we encounter new data confirming the growth of mobile app usage and total hours spent interacting with them. In the 2015 U.S. Mobile App Report, the CoreMetrics team has shared some useful data metrics regarding digital media consumption growth and app usage. A couple of notable themes or trends are:

  1. Americans across all age groups spend increasing time on Mobile Apps
    By mid year, the average american had spent approximately 68 hours/month on their mobile device. That number rises even further to over 90 hours/month among millenials.
  2. A whopping 50% of time is spent within a single App and about 90% on the top 5 Apps
    Not only is the average time spent on mobile App usage increasing, it is concentrated in a few limited Apps. A staggering 50% of their time is spent working within a single App and that number tapers off rapidly as popularity, utility and quality decreases.
    Share_of_App_Time_Spent_by_Rank_Chart_reference

It is evident from this data, that as a Mobile App Developer you want customers to include your App on their home screen. That means not only having a compelling utility but ensuring that the App is of the highest quality. In the rest of the article I will illustrate how you can accomplish just that by incorporating mobile customer feedback loops in every stage of the development cycle and involving and engaging customers through your path to production. Along the way we will also look at various open source and commercial tools that enhance the ability to collect feedback at various stages of the continuous delivery pipeline.

Typical Continuous Delivery Pipeline

Most agile or lean software organizations have an automated continuous integration and delivery pipeline that helps manage the flow of release artifacts to production. While there might be nuanced variations across teams and enterprises the typical path to production for Apps or Services is represented through the steps shown.

newstar devops ci_cd_pipeline

It will be useful to review this pipeline as we explore options to incorporate feedback throughout the path to production.

Continuous Delivery – Collecting Mobile Customer Feedback

Not too long ago, most negative user feedback consisted solely of poor ratings, comments and rants on social media platforms. Without having context, metrics and data, most development teams were left guessing on how best to reproduce and determine extent of the issue. This usually resulted in issues and features getting prioritized in an ad hoc manner.

Today numerous open source and commercial tools are available that help solve the feedback problem. Most of them can be categorized in the following broad areas:

  • Instrumentation
    Despite recent reports that Facebook made it’s Android App crash to test user loyalty, most App crashes are not of the deliberate nature. There are a plethora of crash testing and reporting solutions, the most popular being Crashlytics (part of Twitter Fabric), Apteligent (formerly Crittercism), TestFlight (Apple) and HockeyApp (Microsoft). They each provide a client side SDK to capture and report crash reports and a server side service to to manage and analyze those reports.
  • Phased Releases – Alpha, Beta, Staged Rollout
    Android Application Developers can take advantage of the alpha, beta and staged rollout capabilities available as part of Google Play. For alpha and beta tests, production APK is not required. Developers can avail of different options to target specific groups for their alpha and beta tests. They can also avail of feedback channels available within the App to obtain feedback.Staged rollout allows a developer to progress from alpha and beta testing to production in a phased manner, constantly collecting feedback and metrics, comparing against baseline (if available) and progressing to 100% in production based on satisfactory results. Developers on the iOS platform can avail of beta testing capabilities provided by TestFlight and can invite upto 2000 beta testers via email to test the App pre-production.
  • Direct In App Feedback
    Gone are the days when email, messenger or App store comments provided the only semblance of feedback. Customers increasingly expect to communicate via the app, and provide feedback without leaving it. Meanwhile Mobile App Developers have better to tools to scale that feedback and manage it effectively to address bugs, prioritize features and get context – screen shots, system information, etc. – for specific feedback.HelpStack is an open source framework that makes in app customer feedback relatively easy. Report issues, attach screen shots, embed device information and more. Customer feedback can be reported via email or help desk integrations are available.
    Apptentive, Crittercism, HelpShift, UserVoice, and Parature are some of the notable commercial solutions that enable In App Feedback.
  • Metrics & Performance
    When business analytics do not provide provide adequate answers, diving deeper into technical data might provide insights into what is going wrong. Two key mobile customer feedback metrics worth tracking is app uptime and performance. App uptime helps identify customers facing crashes while performance issues could be impacting engagement rates. Some of the tools mentioned in this article do provide an APM solution that enables monitoring of these key metrics.
  • Experimentation & Analytics
    A/B Testing or multivariate testing is a data driven experimentation approach to promoting app feature changes. While some of the above tools enabled you as a developer to better listen to your app community, A/B split testing allows you to validate your hypothesis and invest further in features and capabilities that demonstrate lift.
    Apptimize, Optimizely and MixPanel are few of the available commercial products that offer multivariate testing capabilities that can be incorporated in some situations without code modification or App updates. They also provide abilities to compare test campaigns against baseline and promote features that demonstrate positive feedback.

Incorporating Mobile Customer Feedback In Continuous Delivery

Leveraging data driven tools throughout the continuous delivery pipeline increases the odds of a quality and high utility mobile app. Even in situations where it is not possible to expose apps prematurely, it is possible to dog food your app – a term referencing a team or company that actively utilizes it’s own product with the intent of testing it. For example, frequent builds tied to developer commits enable alpha build testers and other team members to download and test the App. Meanwhile beta builds can be downloaded by other members of the company. As release candidates emerge the beta community can be expanded to include members of the app community.

mobile customer feedback

So take steps to incorporate mobile customer feedback loops at every step of the development cycle and garner a majority of the app users engagement time. Would love to hear how you and your teams are leveraging tools and techniques to build better apps and continuously listen to customer feedback.