CloudAmp’s Google Analytics Campaign Tracker launches on the AppExchange

Today we are proud to announce that CloudAmp’s first application for Salesforce, the Google Analytics Campaign Tracker, has gone live on Salesforce.com’s AppExchange.

CloudAmp’s Google Analytics Campaign Tracker lets you know exactly which campaigns and sources are producing your leads. It is designed to capture data from the familiar Google Analytics Campaign URLs  into Salesforce via Web-to-Lead forms, so you can know which leads resulted from which advertising campaigns or web site referrals.

If you tag banners, search engine campaigns, email newsletters or links on external websites with Google Analytics Campaign URLs, when visitors click on those tracked items they arrive on your web site with a referral URL that contains those parameters (utm_campaign=, utm_medium= etc.). Now with the Google Analytics Campaign Tracker, you can capture those values into Salesforce when that visitor submits a web-to-lead form, and forever know how you got that lead.

The Google Analytics Campaign Tracker also contains a dashboard and a number of reports, for a turnkey way of analyzing your data once you start collecting it.

Try CloudAmp’s  Google Analytics Campaign Tracker today, free for 30 days.

Only $49/company/month after the trial.

July Salesforce Integration & Analytics Meetup

For the third Salesforce Integration & Analytics Meetup, we had some great networking followed by two presentations: a Salesforce Joined Report demo from Deepa Patel, Salesforce MVP and owner of Halak Consulting LLC and a Salesforce Streaming API & MuleSoft Demo from David Thomson, Salesforce architect and Integration Strategy Lead for MuleSoft

Salesforce Integration & Analytics Meetup, July 18, 2012

Thanks to MuleSoft for sponsoring the event and providing food and drinks, to Rackspace for providing the fantastic meeting space in their SF office, and to CloudAmp for organizing the event.

This event is free and open to all. To join the meetup and learn about future events, please click here.

About our Speakers

Deepa Patel

Ms. Patel is a Salesforce.com MVP and owner of Halak Consulting LLC. She has extensive experience implementing Salesforce, as well as knowledge selling software, building partner relationships, consulting on business and technology implementation strategies.  She has built a team of consultants to provide exceptional service to companies of all types, with a particular focus on legal and financial services firms. She worked in the Mortgage Industry for eight years, sold data warehousing software and has been providing business and technical consulting services for the last ten years.

Ms. Patel will be demoing Salesforce’s new joined reports functionality, introduced in the Spring 2012 release, and providing some tricks and tips for using this powerful new format. The joined report format lets you view different types of information in a single report. A joined report consists of up to five report blocks, which you add to the report to create multiple views of your data.

David Thomson

The Salesforce Streaming API enables near real-time processing of data, allowing for new and innovative applications to be built on top of Force.com. MuleSoft is the first company to support the Salesforce Streaming API, and has enabled its use in environments as diverse as Facebook, JP Morgan, and UCSF. In this talk, David Thomson, a long time Salesforce architect and Integration Strategy Lead for MuleSoft, will show what sorts of new applications can be built with the Streaming API.

CloudAmp Presentation at the Freemium Meetup

The Freemium Meetup was held June 14, 2012 at Pillsbury Winthrop Shaw Pittman LLP in Palo Alto. After an introduction and an overview of Freemium as a business model by Cynthia Typaldos of Kachingle, presentations were given by Don MacLennan of AVG and David Hecht of CloudAmp.

YouTube video of David’s presentation, the slide deck is embedded below as well:

CloudAmp presentation  The Freemium Funnel in B2B Sales:

YouTube video of the entire Freemium Meetup (David’s presentation begins at 48:20 in the video):

Startup Salesforce Tip #1: The Founder Welcome Email

This is the first in an occasional series of my favorite sales and marketing tips for startups and SMBs. Enjoy! –David

One easy and effective marketing best practice is to send out a personalized welcome email about a week after customers sign up for your application or service. Ideally this should be a personal note from one of the founders, short with no sales pitch — more of a “checking in / introducing myself” email. And Salesforce makes it easy to do .

The idea is for this email to be much less formal than the typical welcome emails / autoresponders that go out right after signup, and which contain lots of information and links. It should be signed by one of the founders or an executive whenever possible (a Sales or Marketing title will decrease response, depending on the type of customer base), and should contain as much personal contact information as you feel comfortable giving out.

Example:

Hello {!Contact.FirstName}

I just wanted to follow up with you personally, and make sure you were having a good experience using [Product].

Please let me know if I can provide you with a demo, connect you with anyone on our support team, or help in any way. My contact details are below.

Best,

John Smith
Co-Founder
john@company.com
415-MY-MOBILE


This may seem silly or to be a waste of time, but there are a variety of reasons why it is worthwhile.

  • Additional Touchpoint. Some people will realize this is a form email, but it seems less automated than the system emails people get when they signup. This perception will vary quite a bit depending on your target customers, of course (technical people are very different from marketers, B2B very different than B2C). But in general it is a good excuse to reach out to customers which few will object to, and you may get more responses than you would think (it is easy for someone to dash off a quick response to a seemingly personal email).
  • Identify serious customers. Many customers will appreciate getting the personal contact information of a founder or principal, or really anyone at the company, especially in B2B products where having an actual person (or a person beyond a sales rep) could be beneficial to them as they become a serious customer. They may respond to the email, allowing you to further identify them as qualified.
  • Identify unqualified customers. Sometimes people will respond with “your product sucks” or “take me off your list.” Never discount the value of a NO, it helps you get to those who will buy that much faster. Just make sure you update their customer records as unqualified / email opt-out in Salesforce.
  • Identify misconceptions. A few customers will respond with a variation of “I like your product, but I am not going to use it because it does not do X.” When in fact your product does do X, or maybe there is a workaround, or maybe you are coming out with that feature next week. Good to know.
  • Gather additional data. Not everyone will like this one, but when people reply often additional information is available in their email signature, or their gmail address forwarded to a corporate email address that they reply from. Since so many signup processes for web apps these days are trying to be ultra-low friction, requiring just email address and password or less, I like having someone enter this information into Salesforce whenever you can.


When and How to Send

I recommend sending these emails once a week to everyone who signed up in the past week, using the Salesforce “Mass Email” feature (available in Professional Edition or above). After some initial setup, it is a fairly quick process to do it every week.

Salesforce makes it easy to send out the emails, you don’t have to pull lists into an external system, and best of all you can also remove recipients who are already corresponding with a sales rep or other person at your company (filter out based on last activity or visual inspection).

First, create an email template similar to the one above, or create your own to match the positioning and voice of your business. In Salesforce, go to

Setup > Email > My Templates > New Template

Create a new template, add any merge fields you want (I prefer first name with a Hello greeting and no punctuation, so if there is no value in the customer record it doesn’t seem awkward like “Dear”). Be sure to check the box that makes the template available for use.

Second, go to the Contacts tab and scroll down to

Tools > Mass Email

at the bottom right (Assuming you are importing all signups as Accounts, otherwise go to the Leads tab).

You have to create custom views of recipients for a mass email, but each week you can then click “edit”, update the dates, and “Save as” to get a view for the new batch. In the example below, I am selecting accounts that were created in a single week, and then using the filter logic to also select accounts that either have no activity (no calls/emails recorded on the account), or at least that haven’t had activities in the last day (“last activity less than yesterday” in Salesforce-speak).

You should adjust those values to match your follow up and how often you want to contact customers, and you can also add in additional filter criteria (such as Account Type or custom fields that segment your customers such as Plan or product type).

Once you have saved as, you will see a list of customer emails. If you would like, you can manually scroll through them and uncheck any contacts that you don’t want to receive the email. Click next and select your email template, then next and select your settings for when to send the email. I recommend selecting “Store an activity for each message” so anyone looking at the contact later will see that they received the email. You can also choose whether to “Use My Signature” that is in the email setup, or include a custom signature as part of the template.

Click send, and wait for the response.

Then set a calendar reminder, and in one week change the date fields on the view, save as, and you’ll be ready to go all over again.

Caveat: If you are getting more than 500 customers a week, you will need to do this more frequently (Salesforce limits mass email to 500 per day). A lot more than 500 and you probably can’t use Salesforce efficiently for this, so use whatever external system you use for newsletters and other large email volume (Mailgun, SendGrid, MailChimp, ExactTarget, etc.)

But I already get too much email

I’ll leave you with a final tip I’ve seen some startups employ to deal with this, and it is a clever hack that should work for awhile. If you are worried as a founder about getting more email in an inbox already filled with critical emails from customers, partners, and investors, you can set up an alternate but plausible email address. For example, if john@company.com is your primary address, you can set up john.smith@company.com as an alias that goes to a separate box, or even an alias that goes to you and a Sales person who is tasked with responding to customer inquiries.

Then filter email to john.smith@company.com so it doesn’t go into your inbox, and only reply personally when you need to. You are just lending your name and credibility to the email — if you can follow up to responses personally that is great, but if not, it generally is not a big deal as long as someone responds.

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CloudAmp provides Customer Analytics for SaaS companies, directly inside of Salesforce CRM. If you have a trial or free plan, we can show you who your best leads are based on their real-time usage.

New CloudAmp DirectEngage Presentation

Check out our DirectEngage product presentation, now slightly less boring with music and animations thanks to SlideRocket.

Do you know… Which Free / Trial Users are your best leads?

What if you could see… Your App’s User and Usage Data, right in Salesforce?

>> CloudAmp DirectEngage Presentation 

(opens in new window, Flash required)

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CloudAmp provides Customer Analytics for SaaS companies, directly inside of Salesforce CRM. If you have a trial or free plan, we can show you who your best leads are based on their real-time usage.

Pricing Elasticity Fail

Our Apologies. Garage Full.

When your parking garage is full every day by 10 AM, time to test a “new morning special rate.” I hope that special rate was higher. 😉

Pricing Strategy for SaaS and Services

I was working on a post on how to price services, but then I saw this skit on Portlandia, and since it is Friday…. The great pricing satire starts at 0:58, but the entire four and a half minutes is worth watching. So funny because it is true…

You want the “This Changes Everything” plan!

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CloudAmp provides Customer Analytics for SaaS companies, directly inside of Salesforce CRM. If you have a trial or free plan, we can show you who your best leads are based on their real-time usage.

Free Trial Predictive Modeling in 5 Steps (No Statistics Degree Needed)

Most SaaS products have a free trial or freemium plan. If you are serving trial customers, whether in Sales, Marketing, or Customer Support, you need to be able to predict which customers will convert to paid, so you can optimize your customer interactions based on that information.
 
With all the talk of big data and data scientists these days, using a term like “Predictive Modeling” may conjure up scary images – teams of engineers with giant Hadoop clusters, or indecipherable equations covering a whiteboard.
 
But there are easy ways to predict which customers will convert and which will not, using data that you are probably already collecting.

 

 

Step 1: What do the usage patterns of your Best Customers look like?

 

Examine your best customers, and how they are using your product. What usage metrics do they have in common? And when they first sign up, is there a common pattern to how they begin using your product?

 

Every business will have different metrics that define the customers who are most engaged and most likely to convert, and even within the same company you may have differences between customer segments. Depending on the specifics of your product, we want to look at usage metrics like the following:

  • number of API calls
  • amount of data stored,
  • number of servers deployed
  • number of actions taken
  • number of records created
  • number of users per account (or linked accounts)
  • etc.

There are some metrics common to most web applications, which can also be useful metrics to look at:

  • Number of logins
  • Last login
  • Signup date
  • How soon they started using the product
  • Time period they used the product consistently
  • etc.

You may only have a partial idea of what your best customers look like, or be unsure where to set the thresholds for segmenting your customers. That is ok, as you can always adjust the model over time as you learn more, or compare the effectiveness different models. Pay particular attention to how your best customers and most enthusiastic fans use your product, especially when they first sign up.

 

Using all of the information above, define one to three metrics that correlate to your best customers, and determine some thresholds that will categorize how engaged or likely to convert each customer is. For example, customers who have signed up in the last 60 days and created over 20 records, or customers with more than 5 servers who installed a security agent on more than 2 of them.

 

 

Step 2: What about your (almost) Never Customers?

 

The second step is more important if you have a freemium (free forever) pricing tier, but should be well understood for free trials as well. Are there groups of customers who almost never convert, or are generally unqualified to buy your product in some way?


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For example, if you sell a product which can be used by both businesses and prosumers / hobbyists, there may be a segment of your customers who will never upgrade to paid, as they simply don’t have the business need or cash flow to justify paying.

 

This is not to say that these customers never have value. If you are selling to developers or providing open source solutions, having large numbers of unpaid customers can be critical to fostering a user ecosystem. For many B2B products, free users can serve as a long term lead base if they switch jobs and are in a position to use the product at their new company.

 
But given that your resources are generally scarce, you want to focus your sales and support efforts on those likely to convert. Knowing who is likely to be “unqualified” is nothing personal, just an important way to segment customers and prioritize interactions.

 

Step 3: Any Getting Started Trends / Warning Signs?

 

Step 3 may be less important than the previous two, depending on your business, but it pays to think about usage as it relates to time, to complete our predictive model. Are there actions that people take when they first sign up that are an indicator that they are likely to convert?

For example, they complete their profile or create a new project, enter an API key or connect via OAUTH to a 3rd party system, or perform X actions in less than Y days. Those actively looking for a solution that your product solves will exhibit very different initial actions than someone who just saw your company on TechCrunch (and who signs up for everything they see featured there for some reason, regardless of what it is).


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And what about the duration of their usage? For example, one recent SaaS industry survey found that “Free trial users who were still active during day three of their trial were four times more likely to convert into paying users than the average customer.”

 

Perhaps this seems like an obvious conclusion, given that in many free trials 50%+ of signups don’t even bother using the app at all. And another large chunk of users play around for a few minutes and then get distracted, never to return. But if the three day statistic is true for your business, you would want to follow up with those customers more aggressively, or at least send different Emails to those users right away instead of more generic marketing emails later on.

 

Conversely, are there patterns of usage and then decline which are warning signs? Perhaps customers start using your app and then run into problems. They burn through thousands of Emails or API calls and their usage then trails off, or stops suddenly.

 

If you can proactively identify those customers and contact them, there are some real sales opportunities there (often they are having a simple problem, or may have a misunderstanding of your product’s capabilities). This data can also be useful for churn prevention in the future for a customer success or support team.

 


Step 4: Connect your data to your CRM system

 

The next step is to connect your user and usage data from your SaaS / Web App backend database into your CRM system. By integrating your app’s data into your CRM, you gain several advantages.

First, you empower your sales and support people (assuming they are using the CRM) to see customer usage data right where they look at other customer information. Having to log into another system, or viewing customer usage in an administrative web page or Excel sheet that is outside of their regular workflow is inefficient at best, and will result in them not using the data at all in many cases.

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Secondly, you can use all of the structure and functionality already present in most CRM systems to manipulate the data and calculate the predictive models we have set up in steps 1-3. Otherwise, you have to instrument all of step 5 in your app, which is generally not something that Engineering is going to want to prioritize over features in your product.

 

Once all of the data is in your CRM system, a good marketing analyst or sales operations person should be able to customize views, set alerts and triggers, build reports, and more. This both empowers your team to work with their data without engineering help, and makes things more nimble as your company gets experience working with the predictive model and updating the model and associated analytics as it evolves.

 

Step 5: Implement the Predictive Model in your CRM

 

Finally, the fun part. Once your customer usage data is being updated into your CRM system, you can implement the predictive model based on steps 1-3 above. First, we start with the raw usage data that has been imported, and typically create summary or roll up fields which total up those records, giving you some metrics (Total API calls, Total Builds, etc.)

 

Depending on the complexity of your model, those totals may be enough (a predictive model could be a simple as Total API calls > 1000). But often we want to consider several metrics to come up with a “lead score” for your predictive model (for example, Customers who have > 5 GB stored currently but have had >100 GB stored over all time could generate a “storage elasticity” score for those customers, where that metric might be important in identifying a certain type of customer who is likely to convert — or for a different product, likely to churn).

 

A score can provide a more nuanced model, as well as a way to sort or prioritize customer accounts in the CRM system. But whether you build the model from a single metric, or a number of metrics pulled together by a formula, you can then use the model to begin organizing your customers in the CRM system.

 

You can modify the views that certain sales reps see, so unqualified customers don’t show up in their main screen, reducing the signal to noise ratio and making sales more efficient. Views can be sorted by the new predictive model lead score, so the hottest accounts bubble to the top automatically as their usage changes. For certain scores you can use workflow rules or triggers built into the better CRM systems to even assign follow up tasks or send email alerts to your team members.


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Next, aggregating all the usage metrics and predictive scores into reports provides analytics and dashboard visibility for your managers and executives. With customer usage data being updated in your CRM, right where the new accounts are created, you get to see trends and understand changes in customer usage, signups, churn and more, faster and easier than would generally be possible with manual Excel reports. And business intelligence is now accessible to a larger number of people, some of whom can be empowered to create their own reports to derive further value from the predictive model scores and usage data.

 

If you have read this far, think to yourself what visibility you have into trial customers, and how they are using your product. Chances are you can create a predictive model to understand where customers are in your funnel, and improve conversions and revenue, in just a few easy steps.

 

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CloudAmp provides Customer Analytics for SaaS companies, directly inside of Salesforce CRM. If you have a trial or free plan, we can show you who your best leads are based on their real-time usage.

Trigger.io Customer Case Study

Trigger.io provides a cross-platform app framework that is the simplest way to build native iOS, Android and web apps using a single HTML5 codebase. The company’s main product, Trigger.io Forge, consists of a JavaScript API that exposes native functionality such as camera access and notifications, along with a set of tools to build your app for each platform that you want to support.

 

When Trigger.io was preparing to launch Forge, they wanted to have better tools for managing their expanded sales and marketing efforts. And with many developers using their free “Get Started” plan, they wanted to follow up with any customers who were actively using the product.  

 

“We needed to easily see who was using our product, and how they were using it,” said Amir Nathoo, Trigger.io Co-Founder & CEO. “Ours is a fairly new category, so by engaging with our active customers, we can often help them see how the different parts of our product can have a big impact on their apps.”

 

CloudAmp started by implementing Salesforce for Trigger.io, and migrating data from their existing Gmail-based CRM. We then set up our DirectEngageTM customer analytics product, which extracts data from Trigger.io’s Amazon RDS backend, pushes it securely via https to CloudAmp’s servers, and then maps it into Salesforce in real-time.

 

Trigger.io can now see how each customer is using their product, in real-time on an account-specific level in Salesforce, and in aggregate to understand trends and opportunities. Each major user action in the Forge software (Package, Generate, Run, Build) is immediately pushed into Salesforce as a new record, and fields in the account show totals for automatically scoring the accounts, and reporting customer activity.

 

“Before we had an internal web page where we could see a list of active customers,” said Sahil Jain, Co-Founder & CMO. “But with CloudAmp, now we have each customer’s full contact information in our CRM, along with exactly how they are using our software. We can be much more efficient in connecting with customers for sales or customer service.”

 

To complete the project, CloudAmp built a series of reports and dashboards for Trigger.io, to provide business intelligence that anyone in the company can easily access. With the data integration running continuously in real-time, these reports automatically are updated with the latest data on signup trends, active customers, and other key metrics.

 

As the Trigger.io sales team explores the functionality of Salesforce, we are assisting with workflow rules to set follow up tasks, and the new data will make it possible to build models of the top customer’s usage patterns. Those patterns can then be used for segmentation reports and predictive models to proactively identify new signups with a high likelihood of becoming high value customers.

 

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CloudAmp helps software companies centralize  customer engagement, usage and account data in their CRM.

Increase your conversion rates, customer retention, and revenue by gaining real-time visibility into how customers are using your App, directly within Salesforce.

 

First Salesforce Integration & Analytics Meetup

On March 8, 2012 we held the first meeting of the Salesforce Integration & Analytics Meetup, at Rackspace’s new San Francisco office. We had a good turnout of around 60 people, a mix of those interested in learning more about Salesforce and cloud computing, with veteran Salesforce implementation firms and partners as well. 

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After a couple of hours of networking, we had a presentation by David Taber, author of the Prentice Hall book, “Salesforce.com Secrets of Success,” and the CEO ofSalesLogistix, a certified  integrator specializing in improving business processes, policies, and people issues in concert with extending CRM systems.

 

David gave a talk entitled “What’s your next product? Ask the CRM!” that dealt with how CRM data can drive product strategy, how to best find and analyze the product data in your CRM system, and things to watch out for.

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Thanks to our sponsors: CloudAmp (yours truly and the organizer), Rackspace (for providing the office space), and GoodData (for providing food and drinks).

 

Hope to see you at the next meetup! Sign up here to find out more:
http://www.meetup.com/Salesforce-com-Integration-Analytics/

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