Salesforce

• Leads by Status Funnel – Funnel showing the number of leads by status in the given period
• Leads by Industry or Source Funnel – Funnel showing the number of leads by industry or source in the given period
• Converted Leads Bar Chart – Show the number of converted leads over time
• New Leads Bar Chart – Display number of new leads over time
• Deals in Pipeline – Number of deals in pipeline over time
• Value of Closed Deals by Sales Person Funnel – Funnel of sales people listed by the value of closed deals in the given period
• Campaign Win Rate Funnel – Display opportunity win rate percentage by campaign in the given period
• Neglected Opportunities List – Opportunities not contacted within a defined time period
• Opportunities by Probability List – List of opportunities listed by percentage chance of closing
• Recent Won Opportunities – Display a list of the latest won opportunities
• Top Products List – Display a list of top products by sales revenue
• Current Open Opportunities – Display the number of currently open opportunities
• Top Sources Funnel – Funnel of top opportunity sources by number of closed opportunities
• SOQL/SOSL query – Display data from any SOQL/SOSL query, visualised with one of the following widget types:
  • Number
  • RAG Column and Number
  • Trend Chart
  • Line Chart
  • Bar Chart
  • Funnel
  • Geck-O-Meter

Heroku Postgres Dataclips

Display data from a Heroku Postgres Dataclip URL, visualised with one of the following widget types:

• Number
• RAG Column and Number
• Trend Chart
• Line Chart
• Bar Chart
• Funnel
• Geck-O-Meter

Log in to Geckoboard to try them out and let us know your thoughts and what other widgets we should create for them! We’ll be adding more over the coming weeks.
 

The post New Salesforce and Heroku Postgres Dataclips Widgets appeared first on Geckoboard.

About Bit.ly

Bitly is the easiest and most fun way to save, share and discover links from around the web. They call these links bitmarks, and you can use Bitly to remember, curate and share them. Bitly is available via a website, browser extensions, mobile web, and numerous third-party tools integrated with their open public API. Bitly also powers more than 10,000 custom short URLs and offers an enterprise analytics platform that helps web publishers and brands grow their social media traffic.

Photo by: Eye/see

The post How to Innovate Using Data – Geckoboard interviews Anna Smith, Data Scientist at Bitly appeared first on Geckoboard.

Apologies for any inconvenience!

The post Scheduled Maintenance – 3rd May appeared first on Geckoboard.

We recently heard from Jon Norris, Crunch‘s Web Editor, a freelance writer and Editor of the community site Freelance Advisor. He gave us a great overview of how they’re using Geckoboard to bring teams together.

How did you find out about Geckoboard?

I’m an avid tech news junkie, so I think I first heard about the launch on TechCrunch – I signed up for a beta account which we used for a few months, then moved to a proper paid account when we had the need to display more information.

What was the initial reaction of your team after the status boards were placed in the office for everybody to see?

Because our team is split over two floors there’s a bit of dissonance between client-facing staff downstairs and development, sales, design and marketing upstairs. Having these dashboards on a rotation gives us a little glimpse into how things are going for everyone. It lets our account managers and accountants see how healthy the business is as a whole (in terms of website traffic, leads and new clients), and it lets us upstairs see how busy the operations team are. We never really had any idea how much they get done until we could see it on a big screen!

How did you choose your metrics?

Every team set up their own dashboard and chose the metrics most important to them, focusing on one key data point. For example, marketing’s most prominent metric is total traffic across all our domains, for sales it’s new leads and conversion rate, and for tech support it’s open tickets.

How do you think Geckoboard has helped you to improve decision-making throughout the business?

It has made every department more aware of what other departments are up to. Internal communication has been streamlined greatly – our monthly catch-up meetings no longer need to start with a performance roundup from each Manager, as everybody already knows the key figures.

In that sense it has improved decision-making as decisions can now be made within the context of the entire company’s performance, not just an individual department’s metrics. To give you an example, we in the marketing team now have a better understanding of the ebb and flow of our account manager’s caseloads, which are fairly predictable due to the tax calendar. This means we can plan big campaigns for times when their workload is low, giving them more time to bring new clients on board.

What would your advice be to other organizations that haven’t started using this kind of technology, or that are interested in leveraging their current efforts more?

Think carefully about what information to display, and try to avoid ‘vanity’ metrics. Sure, you may be recording 500,000 hits to your website every month, but all those visitors are meaningless if you’re not tracking your conversion rate.

Graphs can be particularly useful for identifying sudden changes that other analytics packages may not pick up. We track response times to our app servers, and a sudden spike is a surefire indicator of a problem, which we can look into straight away rather than waiting to hear about it from customers on Twitter.

Thanks to Jon for sharing his experiences of Geckoboard.

About Crunch
Crunch is an online accountancy firm based in Brighton, England, for freelancers, contractors and small businesses. They provide real-time cloud accounting software and unlimited support from accredited accountants for a flat monthly fee.

The post Featured Business Dashboard – How Geckoboard Helped Bring Teams Together At Crunch appeared first on Geckoboard.

Desk.com

Case Count – Display the number of cases by all or a specific ticket status, filtering by assignee, group, channel, time or priority
Priority Funnel – Display a funnel of cases by priority, filtering by assignee, group, channel, time or status
Status Funnel – Display a funnel showing the number of tickets by ticket status, filtering by assignee, group, channel, time or priority
 

Airbrake

Recent Builds – Display the outcome of the most recent builds
Project Build RAG – Display the RAG status of builds per project
Last Deployed – Show the time since a project was last deployed
 

TeamCity

Recent Build Outcomes – Display a list of recent builds, with the build outcome
Project Build RAG – Display a RAG chart showing build outcomes for a specific project
 

Hosted Graphite

Graphite Graph – Display a line chart showing a Graphite metric over time
 
 

Zendesk

Recent Feedback Comments – Display recent feedback comments, showing all or just positive or just negative.
Satisfaction Rating – Display your current satisfaction rating.
Satisfaction Rating RAG – Display your current satisfaction rating as a RAG widget, breaking down the number of positive and negative reviews.
 

We also updated our JIRA widgets to make them more flexible – they now load in custom statuses and priorities, as well as let you define the RAG entries.

Log in to Geckoboard to try them out and let us know your thoughts and what other widgets we should create for them! We’ll be adding more over the coming weeks.
 

The post New Desk.com, Airbrake, TeamCity, Hosted Graphite, Zendesk and updated JIRA widgets appeared first on Geckoboard.

The post Interview with Brian Kardon CMO Lattice Engines about the future of Big Data appeared first on Geckoboard.

Paul:   I think maybe a great starting point would be if you could do a quick introduction to yourself, and maybe tell us a little bit about your background.

Gregory: Sure. I’m Gregory Piatetsky-Shapiro. I’m currently the Editor and President of KDnuggets. I started as a researcher in machine learning and databases, and got my PhD in 1984. I joined GTE Labs in 1985. GTE was a large telephone company in the US (now part of Verizon), and I was working there on application of intelligent methods to databases. I organized the first workshop on knowledge discovery in databases in 1989, and these workshops grew into the first conference in this area in 1995 (KDD-95) and now into a leading research conference in the field (www.kdd.org), with the next conference, KDD-2013 in Chicago. After GTE Labs I worked at a couple of startups and since 2001 I’ve been an independent consultant in data mining and analytics.

I started publishing KDnuggets in 1993 as a newsletter to connect researchers who attended the workshops on knowledge discovery; there were about 50 subscribers. I added a website in 1994 and created KDnuggets.com website in 1997. KDnuggets is now an influential voice covering the Analytics, Big Data, Data Mining, and Data Science space. KDnuggets audience has been growing and reached over 55,000 unique monthly visitors in the last 3 months, and over 25,000 subscribers via email, Twitter, Facebook, and other social networks.

Paul: How would you describe big data, and what does it actually mean for businesses, and particularly startups?

Gregory: The definition of Big Data I like best is “Data is Big when data size becomes part of the problem”. In addition to size or volume of data, there are two other important parameters, usually mentioned together as the 3Vs of Big Data (first defined by Doug Laney).

1. Volume: think Google-size.
2. Velocity: think Twitter.
3. Variety: think text, images, links, videos, etc.

Those three Vs of big data make analyzing it more difficult, more challenging, and potentially more rewarding than a few years ago.

Google Trends for Big Data shows an explosive growth in popularity of this term, starting around 2011. “Big Data” is also the name of many conferences. Finally, it’s also the name of a Big Data journal that just recently started.  All these meetings and publications try to cover this important trend (more trends and analysis in my presentation Analytics Industry Overview); there’s a lot more data now anywhere than any time before. It’s also a tremendous opportunity for many startups. I think Big Data is a tremendous opportunity, no less significant than the second Industrial Revolution.

 Paul:   An incredibly powerful thing to say. What sort of opportunities do you think startups can make of that?

Gregory: I think the biggest opportunities are in new platforms. Think Google and Facebook, they would not exist without big data. If the number of searches or web pages was very small, there would be no need for Google.  If the number of connections between people was small, there would be no need for Facebook. Google and Facebook are two of the biggest companies, but you can think of local information too, perhaps FourSquare. You can think of recommendations, social media.  Many combinations of mobile, social, and analytics would create very interesting startups.  At the same time, Big Data is also generating a lot of hype – see my blog in HBR on Big Data Hype (and Reality).

Paul: Old businesses, I suppose, can use their own data to become better at their internal processes and become better operationally, also. Do you have any insights on what’s the right balance when you’re talking about using intuition versus data and experience? Where does data fit into that?

Gregory: I think intuition is great if your problem is small or medium-sized. If you burn your hand once, you know not to touch the hot stove again; you don’t need big data for that.  But when the problem and data is big, we usually don’t have the relevant intuition. Again, think of Google; there is no intuition for what would be the right page to answer every query. Human intuition just doesn’t scale for such large problems. When there are lots of examples, lots of instances, lots of connections, big data can provide solutions to find what are the right processes. For example, Big Data can be pretty effective on an individual level, for example in targeting ads, determining which people are likely to buy which product, or switch telephone companies.  However big data does not help when prediction is not on the individual level, but a large-scale system, such as an economy or political event.  We only have one Earth, and we cannot run millions of simulations in parallel universes to create predictive models.  On this Earth, we’ve only had a limited number of big financial crises, and so it is very hard to predict events like the financial crisis of 2008.

Paul: What would you say, in your experience, have been the best mechanisms or process that organizations can adopt to make sure that the data that they’re using is acted upon and not just mounting up in some data warehouse somewhere, or hidden under an analyst’s To-Do list? How can you make sure that insights are gained from that data and that an organization can actually take action based on it?

Gregory: I think you start with the right questions first. You really need to focus on the business goals and integrate the business goals into the entire process and iterate quickly. There is no point in building very large process just for the sake of discovering something interesting if it’s not actionable. Focus on what is actionable, iterate, build prototypes, and try to integrate data from different sources as much as possible. Also, realize the limitations. Not everything is predictable. Big data can improve the predictions, but it will not likely to make the predictions perfect.

For example, the Netflix prize is a good example (details in my blog in Harvard Business Review). Netflix users rank movies between 1 and 5 stars and the Netflix algorithm gives recommendations and estimated ranking.  When Netflix announced its $1 million prize in 2007, the average error between estimated movie ranking and actual user ranking was almost a full star (actually 0.95 stars). The goal of the Netflix prize was to reduce that error by 10%, to 0.86 stars. The two interesting things that emerged from competition were:

1. In just two weeks, several teams exceeded the accuracy of the Netflix algorithm (but only by a little).
2. It took 3 years for the best teams to reach that the goal of 10% improvement. People are predictable, but not completely.

Paul: Is there anything else you’d like to speak about, or is there anything in particular that’s exciting you at the moment?

 Gregory: Big Data and Analytics is a very interesting area. It’s exciting to see tremendous growth in companies, start-ups, research, and applications in this area. Data scientists are very much in demand and have a significant power in helping companies and society make important decisions. However, with power comes responsibility. Should data scientists adhere to a code of conduct?  What should it contain? KDnuggets will be organizing a debate on this topic on Google Hangout April 10, 2013 at 1pm PT / 4pm ET/ 19:00 BST – the exact URL will be announced on KDnuggets about 30 minutes before .

Paul:   Thank you for very much for taking the time today.

Gregory: Thank you very much, Paul. It was my pleasure.

@geckoboard

The post Interview with Gregory Piatetsky-Shapiro: Big Data, Myths and Opportunities appeared first on Geckoboard.

Eventbrite

Number – Display the revenue number or count for sales of all or specific ticket type for an event
RAG – Display the RAG status of the number of tickets sold and un-sold for all or a specific event and ticket type
Line chart – Display a line chart showing ticket sales over time for all or a specific event and ticket type
 

Pipedrive

Recent Deals – Display the last 15 recent deals as a list
Deals Stage List – Display a list of deals at a particular stage, for all or owned by a specific person
 

Sprintly

Stage RAG – Display a RAG chart showing product items by completion stage
Blocked Items – Show a list of product items which are being blocked by another
 

Unbounce

Leads Count – Display the number of leads for a page
Page Stats – Display the number of visits, visitors, clicks, form submits, conversions or the conversion rate for a page
Conversion RAG – Display a RAG status of visitors, visits and conversions
Conversion Funnel – Display a funnel showing visits and conversions
 

Pipeline Deals

Deals by Stage – Display the stage of the last 100 deals for all or a specific user as a pie chart
Deals Won – Display the value of deals won by person or owner as a bar chart
 

SEOmoz

mozScape URL Stats – Display stats for an URL including the number of Linking Root Domains, Total Links, Domain Authority, Page Authority and Pagerank.
 

StatusCake

Performance – Display performance of your site over the last hour
Tests – Show an overview of your tests
 

Basecamp New

To-Do Line Chart – Display a line chart showing the number of closed and open to-dos or the total remaining to-dos for a specific list.
 

Social Media Shares

Delicious – Display the number of Delicious bookmarks there are for an URL and how that number has changed since yesterday.
Pinterest – Display the number of pins there are for an URL and how that number has changed since yesterday.
LinkedIn – Display the number of LinkedIn shares there are for an URL and how that number has changed since yesterday.
Twitter – Display the number of Twitter shares there are for an URL and how that number has changed since yesterday.
Facebook – Display the number of Facebook Likes there are for an URL and how that number has changed since yesterday.
Google+ – Display the number of +1s there are for an URL and how that number has changed since yesterday.
 
 

Log in to Geckoboard to try them out and let us know your thoughts and what other widgets we should create for them! We’ll be adding more over the coming weeks.
 

The post New Eventbrite, Pipedrive, Sprintly, Unbounce, Pipeline Deals, SEOmoz, StatusCake, Basecamp and Social Media widgets appeared first on Geckoboard.

Here’s some really useful tips:

What does it really mean to be a data driven company?

If I really had to boil it down, I think being truly data-driven is all about listening, even when the numbers tell you things you don’t want to hear. Many companies claim to be “data-driven”, but that seems to mean that they create metrics that back up what they already believe or help justify the existence of some manager or department. Being data-driven isn’t about collecting a mountain of data to hide your problems with – it’s about asking honest questions and finding the right numbers to answer those questions.

In the context of marketing, what are the typical challenges in choosing the right metrics and what can we do to facilitate that process?

I think one of the biggest challenges is that not every metric suits every situation or audience. What the CEO needs to see and what content marketers, social media managers, etc need to see can be very different. Ultimately, it’s a question of (1) how much do you simplify, and (2) how do you end up with something that’s actionable (and not just looks nice on a PowerPoint slide). They’re both balancing acts – if you don’t summarize enough, you can’t act. If you summarize too much, you might miss something useful. I think the key is to never treat any one metric as sacred. Any measurement or summary is just one point-of-view.

What would you suggest are the best mechanisms or processes that startups can adopt in order to make sure that data is actionable and acted upon?

Don’t get hung up on perfection. You’ll never find the ultimate metric, and you’re going to have to evolve along the way. Pick something actionable, build a goal around it, and try something. Spending two years deciding which metric to use can be worse than no metrics at all. This means you have to accept a certain amount of flexibility and even forgiveness. Measure success in modern marketing channels is tough, and you shouldn’t fire everyone after three months because they can’t live up to your first attempt at measurement. Metrics should allow you not only to measure success, but to adjust to failure and improve. It’s an ongoing process.

Could you tell us a little bit how do you go about making sense of data and making sure those insights are communicated?

Even when I’m wearing a data science hat, I always try to have a question to answer. I think it can be dangerous just to hand someone a pile of data and say “Here – find something!” Our obsession with “big data” is only making that worse, in my opinion. Data can hold answers, but you have to ask the right questions.

As you saw in our recent report, a lot of startups struggle when choosing their metrics and then acting upon them. Could you offer some advice on this?

I think step one is to pick something that sounds sane and accept that you’re going to have a few missteps. If I had to generalize, from a marketing mindset, I’d say to start with at least one “traffic” metric and one “conversion” metric. Ultimately, sales depends on how many people you get through the door and what percentage of those people buy what you’re selling. Pulling one lever or the other isn’t enough. What exact metric you use to measure each of those can be very situational, but if you’ve covered both sides of that equation, you’re off to a good start. Once you’ve got that down, you can start looking at things like lifetime value, but everyone has to start somewhere.

Many thanks to Pete for sharing his advice with us. Find out how SEOmoz creates excitement for data with their marketing dashboard. You can also watch our latest interview with Ben Yoskovitz Lean Analytics author on The One Metric That Matters

@geckoboard

The post Making Sure Data Is Actionable. Guest Post by Peter “Dr. Pete” Meyers. Marketing Scientist at SEOmoz: appeared first on Geckoboard.

We recently heard from Triin Linamagi, Key Account Manager at TextMagic, a bulk SMS marketing firm. She gave us excellent insight into how they’re currently using Geckoboard, read on to learn more.

A Bulk SMS Marketing Firm With A Problem

TextMagic used to have a data problem – as a rapidly expanding company they needed to keep track of sales and other key statistics but that involved a lot of work in accessing different sources – Google Analytics, Pingdom, SEOmoz, as well as their own database, emails and ticketing system. All these different systems made it hard to quickly view their most important KPIs.

This was causing difficulties, as Triin explained “we are a very busy company that develops and markets web and internet based text message software and services for businesses, a service that is increasingly in demand – but we were wasting too much time on keeping track of everything! Then we discovered Geckoboard…”

A Workplace Revolution on a 46″ Flat Screen

“Geckoboard has simplified the way we consume business data. We are now able to look at everything at once, giving us a complete overview of the business at a single glance and saving us a huge amount of time. Each of our team members can monitor what is happening – so sales, marketing, and customer services all have their own section of Geckoboard where they can see key data relevant to them in real time. Everyone gets involved and the real-time dashboard keeps us motivated – we know our targets and can see at any point whether we are on the right track for achieving them. It also means that we are able to react quickly if something appears not to be working, or indeed capitalise on a new initiative that is setting sales figures or website visitor numbers alight. At our office we use a large Samsung flat screen TV to display our Geckoboard data and then at home we are able to go online via our tablets and still see how the business is doing.”

TextMagic use Geckoboard to display the following key metrics:

• SMS texts sent each day
• SMS texts sent each month
• New users recorded each month
• Churn and net accounts growth
• Daily sales
• Year to date sales
• Website visits via Google Analytics widget
• Website uptime monitoring via Pingdom widget

Keeping TextMagic Flying High

Triin says that “Geckoboard has been a huge success for us – we can now track all our vital key performance indicators easily and efficiently and certainly won’t be going back to our old tracking methods. The flat screen with our real-time dashboard goes dark only on weekends – on business days it is always on.”

“A good comparison for how it works is that of an aeroplane – a plane’s instruments and the data they show are vital for keeping it in the air, but the pilot needs to be able to see them all at once. The same is true for a business – having everything in front of you enables you to react quickly and make changes before you hit the ground!”

Thanks to Triin for sharing her experiences of Geckoboard.

About TextMagic
TextMagic provides text messaging products, develops and markets web-based SMS communications solutions for businesses, agencies and developers. TextMagic bulk SMS services are fast, reliable and have worldwide reach, helping clients get the most from their SMS communications budgets.

The post Featured Business Dashboard – How Geckoboard Helps TextMagic Keep Up With The Pace of Change appeared first on Geckoboard.