Monthly Archives: Sep 2012

How Blank Label uses Klaviyo to Increase Sales via Better Customer Lifecycle Management

We recently sat down with Fan Bi, Chief Shirt at Blank Label, to learn more about how they are using Klaviyo to improve their marketing and better understand their customers – as well as to learn more about the joys of a custom dress shirt.

Tell us a little more about Blank Label…

Blank Label is a custom dress shirt brand. We exist to help men be better. Custom is for those who appreciate the fit and finish of something made for their body, not for a hanger.

What does Blank Label use Klaviyo for? 

We have two main uses of Klaviyo:

1. To better understand our customers’ behavior. With Klaviyo we are able to segment our 13,000 plus customers with almost every combination of filtering, from where they came from, how much they’ve spent, whether they’ve required customer service help, etc. From there we’re able to answer interesting questions, including:

  • Did customers who originated from Google spend more than those from Facebook over the last 6 months?
  • Did customers who received email newsletters spend more or less than those who did not?
  • Etc

2. With those various segments created in Klaviyo, we can then email them individually directly from Klaviyo. Rather than sending just a generic email newsletter, you can send a much more personalized message based on, for instance, the fact they have purchased three times in the last year but not in the past six months, or that they’ve purchased a five times in the past three months and you want to send them a thank you email.

Who are some of the key groups of customers you focus on in Klaviyo?

We have created over 20 groups of customers in Klaviyo to focus on – everything from filtering based on amount customers have purchased, the time period they’ve been a customer, and how long a customer has been inactive.

The most interesting group is perhaps one defined as “high spenders who haven’t spent with us in 180 days”. Our top quartile of customers make up a significant portion of our sales and so we can now be much more on top of them churning, and do everything possible to get in front of them before they completely turn away.

How has Klaviyo changed what you do on a daily basis? 

We were doing customer segmentation based off of a couple of variables all in excel. What used to take me 5 hours now takes 5 minutes, and I’m able to get an order of magnitude deeper analysis.

Once customers have been emailed, Klaviyo tracks how their customers behavior changes over time.

What are some of tangible impacts you’ve seen on your business and customers?

Our quantitative analysis has shown us that we’ve been able to recapture at least a couple hundred of lost, inactive customers just by using Klaviyo in the past several months.


Try Klaviyo today with no commitment to see how it can help you better understand and market to your current customers.

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Don’t Fear what you can Measure (and an idea for improving Email)

All of us make a ton of decisions everyday, but most of us also spend a lot of time not making decisions – debating the merits of doing A or B, questioning a decision we’ve made, etc. This debate doesn’t really make sense – in many cases, just trying something out and then measuring the outcome is the most effective, efficient and valuable way to make the right decision.

Let’s take email as an example (though the same idea is relevant to many of the other decisions we make on a day to day basis).

The Problem of Email

Email is a problematic – it’s overwhelming, it’s annoying, it shows up whether we like it or not, but it’s also the most effective tool businesses have to communicate with users and customers.

The real problem with emails for most businesses is that the fear of the downside of email (becoming annoying spammers) is not justified by the risk it takes to test emails to actually know their impact and what customers like. In short, we can just take a subset of people and send them different emails, more or less emails, etc and see how their behavior changes (and even assess their customer happiness).  This isn’t how most companies do it – instead they either A.) just spam the heck out of us or B.) stick to the most basic and minimal of emails, even when more emails might be helpful to the customer.

Be More Creative, but use Analysis to see what Happened

The core idea here is that rather than companies just keep doing what their doing or doing nothing, they could just go out and try ideas and see what happens. I’m not talking about comparing slightly different message content here – I’m proposing comparing radically different approaches, such as:

  • Not sending users emails
  • Sending personalized emails individually
  • Sending only trigger based emails (you’ve done X but not Y so here’s how to do Y)
  • Sending one more / one less email
  • Sending more casual emails

What does it take to know what the impact actually is?  Not as much as you’d expect.  If you are a web app with 100 sign-ups in a week and devote 20 of those to testing new ideas, you’ll start to gain real data into what new approaches would actually do. If you see one being successful, you can expand the test, run it for longer, etc.

Stop Pointless Debates

I used to work with a large web storage company that was in the midst of a long debate about whether to collect more information about users during sign-up. The core issue was whether the value of knowing the information (which allowed targeting emails and better support) was higher than the lost customers who wouldn’t want to answer the question.

There’s no reason to sit around debating this for months when you can find out the right answer by taking a small subset of new sign-ups and treating them differently.

Get Sh*t Done

In summary, if you can cheaply and easily test something, it’s better to see what actually happens than to sit around debating it.  Email is a great candidate for this – it’s cheap, easy to target, directly reaches customers and for most businesses on the web is a huge area of improvement.


Klaviyo is a new kind of CRM that can handle this entire process – seeing your customer behavior, sending emails and understanding their impact.  Try it today with no commitment.



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A Look at Klaviyo’s Integration with

One of Klaviyo’s key strengths is in allowing our clients the ability to quickly and easily add existing sources of customer data with no code and just a few clicks.  Unlike a typical CRM, Klaviyo is much closer to a “full-box” crm that lets companies leverage the data in their marketing, help desk, and other tools. Once information is integrated, Klaviyo gives businesses a complete customer profile in one place and the tools to easily identify customers based on things they have or haven’t done and then to target them with marketing.

The Klaviyo / Integration

One integration recently launched (and being actively used) by our clients is with Klaviyo’s integration gives our users details on tickets and their current states for each of their customers – side by side with purchase, usage, and all other info on that customer.

Having this information enables identifying and targeting groups like:

  • Ecommerce companies could find all customers who haven’t purchased in the last 6 months and have no open support tickets, and send them a coupon to return
  • Software firms could find all customers who signed up in the last week, filed a support ticket, and haven’t used the product since, to send a personalized email
Once groups are created, they can easily send targeted emails to groups and measure the impacts of those emails over time.

How to Setup the Integration

Adding data to Klaviyo can be easily completed in just a few minutes.

Step 1: Go to the integrations page in Klaviyo and select

Step 2: Follow the on-screen instructions to complete the integration.  In short, all you need to do is login to and follow the clear instructions on creating a new API application – but we’ll walk you through this every step of the way to keep it really easy.

Together, Klaviyo and help you send smarter and more effective emails to your existing users based on what they have and haven’t done to drive greater lifetime value and higher customer happiness.

To get started with Klaviyo and, click here.

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The Big Data Value Gap and What it Means for Boston

Big data is likely the most hyped term in tech of the past two years; however, amidst all the hype, we may have actually missed the point of having all of this data in the first place: to generate more value for businesses and consumers. Importantly, it’s this gap between hype and value that speaks to why Boston might be at center of what’s next in data and analytics.

Why We Have Data – Big or Otherwise

What’s often lost in the big data discussion is that data and analytics tools generate no value until they lead companies or individuals to make different (and better) decisions than they would have made otherwise.  While we do occasionally read about big data success stories (for example, Target’s marketing to newly pregnant women or’s health monitoring), most companies still aren’t clear on how they actually could use big data to impact their business. For data to become valuable, companies need to have a direct path from that data and analysis to tangible action.

The Unique Position of Boston

As companies start to look beyond buzzwords to value, the unique qualities of the Boston ecosystem put it in a powerful position to have a major impact on how data and analysis get turned into action.

Boston combines three key qualities that don’t occur together elsewhere:

  1. Boston has world-class data and analytics expertise. From university research groups like MIT’s bigdata@CSAIL to the more than 100 big data companies in Massachusetts, the ecosystem around Boston is uniquely endowed with deep knowledge of the technologies used for data collection, storage and analysis.
  2. Boston has a critical mass of leading marketing software companies. From more established companies like Hubspot, DataXu and Constant Contact to new companies like ThriveHive or GaggleAMP, Boston is filled with companies focused on helping marketers generate measurable business value by using their software.
  3. The Boston startup and investor scene is highly revenue focused. As the stereotypes would indicate, Boston’s investors and entrepreneurs are more likely to be focused on companies generating measurable revenue quickly than their west coast counterparts historically have been. This means that companies are more likely to solve immediate problems for paying clients.

In short, Boston’s emerging companies have the ability to draw on a wealth of technology and data expertise, as well as significant experience using software to drive immediate business value – all while being healthily pushed to find paying clients to generate revenue.

A Personal Experience

Klaviyo, the company I co-founded, is proud to be a part of this movement in Boston, and we wouldn’t exist without the unique Boston qualities described above. Our focus is on helping our clients better understand and market to their customers based on things those customers have or haven’t done – whether that’s helping software firms find users who may need more help getting setup or helping Ecommerce companies reach out to customers who haven’t purchased in awhile to offer them a discount.

In our case, the data volumes we deal with are what many would consider “big” (since we let our clients combine customer interactions ranging from emails opened to items purchased to features used in a single place), but our core reason for being isn’t the size of our data – it’s that we can generate real business value for our clients by solving the problems they were already struggling to solve.

An alternate version of this appeared on BostInno as a guest post.


Try Klaviyo today to drive higher conversion and greater lifetime value for your existing customers through better marketing based on what customers have or haven’t done.

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Freedom of Data + Subscription Models => CRM for the Web

In April, Jon Bischke wrote an excellent article on Techcrunch entitled “The Rise of Full-Box CRM”.  In short, Jon describes a future where CRM systems come populated with potential leads right out of the box – with no need for manual data entry. While Jon does a great job of capturing how LinkedIn and Rapportive may change who is in your CRM at the start, there’s another “Full-Box CRM” movement afoot about what is in your CRM initially – and this movement opens the door for CRM’s for the web that fundamentally change the relationship between companies and their customers.

The Freedom of Data

First, as usage, email, help and other customer data become more free (easier to pull out of the systems it was generated in), CRM’s can be pre-populated with a complete picture of your customer interactions almost immediately with minimal technical work. Companies like Mailchimp,, Zendesk, Shopify and even existing CRM solutions all become incredibly valuable inputs that pre-populate a broader CRM that gives everyone in the organization the ability to use and interact with this information. No matter which system generated the data, teams across organizations can now have access to it.

The Rise of the Subscription Web

While the freedom of data allows a pre-populated CRM, a separate trend is that more and more companies on the web are moving to subscription models – whether that’s enterprise software or Netflix style models that charge a monthly fee or more subtle loyalty based models like mobile gaming (where users have to keep paying to keep playing). Whereas companies could previously rely on initial sales to drive most of the revenue, in this new world, current customers are likely a significantly larger source of revenue than new customers.

The Dawn of CRM for the Web

As these trends intersect, there’s a significant opportunity for a CRM that allows customers on the web to receive personalized treatment from web companies based on where they specifically stand in their customer lifecycle.

CRM for the web requires several key features:

  • Incredibly easy data integration since data is too large to be manually entered
  • Strong prioritization since you only have time to focus on a subset of customers
  • A direct and repeatable tie to taking action since customers are too numerous to reach out to individually
  • Measurable results since you ultimately need to automate your outreach

With the advent of CRM for users on the web, companies will be able to focus on building happier and more loyal customers, which is good for both companies and for users.


This is the future we’re working on at Klaviyo. Try Klaviyo’s CRM for the web with no commitment in our 14 day trial.

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The Experience beyond the Product: An Intro to Customer Lifecycle Management

When we talk about great products, we often focus only on the product itself; however, we forget that for the customer, their experience is actually defined not just by the product but by every interaction they have with us.  Take my Apple Iphone – the in-store experience, the packaging, the setup, the support after I dropped it in the ocean – everything has gone to making it an excellent customer experience almost every day.

This is where customer lifecycle management comes in: at each point in the customer’s experience, how should they feel and what is it that they should do next to become an even happier customer?

Because we can build products really quickly on the web, the experience beyond the product is often an after-thought; however, if we’re really going to build experiences people love, it really matters. The goal of this post is to help frame our thinking as we think through how to build that experience using the Iphone as a case study.

The Iphone Customer Lifecycle

Let’s look at the first few phases of Iphone ownership:

  • Getting the phone setup
  • Configuring Email
  • Making your first call
  • Adding Contacts
  • Installing your first app
  • Buying your first paid app

The key thing to note is that each phase is defined in an action (something Apple would want customers to do), and not just a time frame (which sadly is how the web mostly works currently with drip email campaigns). For the Iphone, I’m guided to the next phase in many subtle ways – by employees in store, by ads in Itunes, by emails I receive and by the phone itself (via prominent app store and email buttons).

Why this matters and what You should do

Unlike the Iphone, most web apps don’t lock you into multi-year contracts – so if people don’t reach a phase, they might leave. A simple way to get started thinking through your phases is to use your successful customers as a starting point.

Some questions to consider:

  • What makes a successful customer? If you look at your happiest customers, what do they look like?  How do they use your product?  What’s different about them vs people who don’t do as well?
  • What has a successful customer done by day 2?  By day 7? By day 30? Now – rewind the clock.  What does that customer look like earlier in their relationship with you?  Are they the one who’s logging in multiple times a week?  The one who adds data right away?

You probably won’t know the answers (and over time you can use cohort analysis to get a much better answer), but just thinking through this initially gives you a good starting point.

Pulling it all Together

Based on what successful customers have done, you now have both the phase (the customer should have done X) and a point at which you might want to reach out to them (successful customers have usually done X by day Y – so if you haven’t done it by Y-1, it might be a good time to email the customer).

The great thing about this way of thinking is that:

  • You always have a next step for each customer
  • You have a measurable way to determine how a customer is doing

Once you’ve got a few ideas for the phases and days above, start to experiment with reaching out to users based on what they have or haven’t done.  Perfecting it may be as difficult as rocket science – but doing it pretty well is infinitely better than doing nothing at all.


Klaviyo helps you easily identify and target your customers at every stage of the lifecycle. Try it for 14 days today with no credit card!

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Big Data vs Intelligent Data (and what Startups can do with it)

Depending on your perspective, big data is probably the coolest or most annoying buzzword of the last year (though growth hacking definitely gives it a run for its money).  That said, on a personal level, I’ve wondered how applicable “big data” is to your typical web startup (and directly to what I’m doing everyday at Klaviyo).

I’ve come to believe that for most companies today, it’s more important to have “intelligent” data (taking a huge amount of data and reducing it to the right data) rather than “big” data (being able to analyze all of the data you have).

A few reasons that “big” data may not actually matter for many use cases:

  1. Statistics mean we can draw very good conclusions from a subset of the data. Having a million data points isn’t necessarily that much better than 10,000.
  2. Taking action requires that we reduce complexity – recommending a different action for each of a million customers may not workable (or equally likely it doesn’t provide enough incremental value to make it worth dealing with). If we can’t translate data and analyses into actions (that we wouldn’t have taken previously), then they aren’t useful.
  3. Access to more types of data (particularly new data sets) means we can be highly selective about what data to base our actions off of. A great example is calculating a customer’s happiness (and ultimate likelihood of churning). Because I can use API’s to pull together email, support and usage data to easily combine data into a single model, I can actually make a better prediction with fewer variables needed.

What is Intelligent Data

I’d offer a few specific criteria for what makes intelligent data:

  1. Data that is clear and unambiguous – i.e. the data values can be defined and measured in a repeatable fashion
  2. Data that is concise – i.e. the data represents the smallest number of data points that would lead to the same action. If you need 90% certainty to take action, it’s the amount of data that will safely give you that.
  3. Data that is directly linked to action – i.e. based on different values of that data, different decisions will be made and implemented.

In short, intelligent data is data that is a direct input to analysis – and very specifically to the right analysis needed to decide between decision A or B.

How Startups can use Intelligent Data

There are numerous web applications actively helping companies use intelligent data. Unbounce or Myna (for A/B testing), Hubspot (for marketing analytics), Klaviyo (for user management and marketing), and countless others.  The key for anyone to take advantage of intelligent data is to think clearly about what data means and what you’re going to do with it.  Only in the doing does data actually start to matter.


Try Klaviyo today to see how we help you use intelligent data to help you manage and market to your customers.

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Our Show HN Aftermath: Lessons for Managing Users and Onboarding

Last week, we posted a “Show HN” link to Klaviyo’s feature tour on Hacker News (post is here).  Our post spent ~4 hours on the front page of Hacker News and resulted in:

  • ~1,500 visits directly from Hacker News (as well as a several day halo effect)
  • numerous helpful comments, emails and chats
  • a significant number of new sign-ups

Our goal was to get useful feedback, and it certainly scored on that front.

Coming up on a week later, we thought it would be useful to step back and give an overview of what we’ve done since that day – particularly in regards to how we’ve managed the sudden jump in the number of customers in trial.  In this case the Show HN sign-ups is just a case study – these lessons should be useful for everyone thinking about customer onboarding.

The Initial Analysis of New Sign-ups

Our first step after getting a bump in sign-ups was to take the full list of new sign-ups and scan it for people we knew, people who signed up with fake emails or people we thought were different (as an example, this group would include bloggers, investors, etc – people who probably couldn’t be actual users but were still interested). We put all of these folks in a group, left them out of our “standard” communications plan and handled next steps individually.

Grouping New Users by their Next Steps

Our second step was to create standard groups so we could easily know where each new sign-up stood in their trial lifecycle. The goal here is that each user is in one (and only one) group, and for each group there is a clear next action to be taken.

For us, this looks something like:

  • Signed up in last week, hasn’t sent data – We know sync’ing up usage or 3rd party data with our system is a key first step.
  • Signed up in last week, has sent data but hasn’t created a group – Once a user adds data, creating a group in Klaviyo is a key way for users to generate value for themselves by doing something they couldn’t do without our software.
  • Signed up in last week, has data and created group – Once people are up and running, we start to focus on both introducing them to a broader range of features and getting their feedback of ways we could better serve them.
  • And more (I’ll spare you an exhaustive list, but we’ve basically mapped out groups for each stage of customer lifecycle – i.e. trial ending in next three days and very low usage, existing users with frequent logins, etc).

Why User Groups are Crucial

Having these clear groups is really, really helpful for a few key reasons:

  1. It keeps us focused on the users and actions that need attention. A user sending us data for the first time is much more important than the user who integrates a new data set once a week. By focusing on groups of customers, I can take an overwhelming amount of usage and customer data and make it actionable.
  2. It lets us personalize emails based on what people need to do next. Rather than just saying “here’s what the average user needs to do at this point”, we can be very direct and helpful “here’s what’s useful for you at this point”.
  3. It helps us find failure points in our onboarding. By keeping users in groups based on actions they need to do next, we start to get a picture of which users ultimately convert, how long they spend in stage, etc. By knowing which groups are problematic, we know where to focus our energy – whether that’s making product changes or changing the way we communicate with users.

How to Get Started

To do something similar, you need to A.) think through your customer lifecycle to come up with initial groups and B.) come up with an easy way to quickly see who’s in which group.  In our case, we used our own tool – Klaviyo is built to help you create groups, monitor them, and take action via email; however, you could certainly build your own system to do this.

In terms of coming up with the right groups, we’ve found it’s best to take a series of initial guesses and then to refine them over time.  The key thing is to make sure that the definition of what puts someone in a group is extremely clear and that there’s a clear common next step for group members.

We may be biased, but using Klaviyo makes this whole process incredibly easy.  Sign up for a free trial now.


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