Is the channel ready for Big Data?

Rod Jacka - Monday, August, 27, 2018

Check out MD Rod Jacka’s opinion as he weighs in on the subject in CRN Magazines August 2018 feature.

When the concept of big data first burst onto the scene earlier this decade the focus was largely on the very big problems that very big organisations could tackle using very, very, big data sets.

Over time big data has shrunk a little. The tools that enable analytics have become more commoditised, affordable and, therefore, applicable to more modest projects.

But while the tools themselves might now be better suited to Australia’s 250,000 or so mid-sized enterprises, channel companies aren’t yet developing big data practices.

Why not? Because the opportunity in big data may not be the one that everyone expects, according to the Sydney-based managing vice president at Gartner, Ian Bertram.

“The opportunity is to sell how to increase data literacy and the ability to use the data that [clients] have got,” Bertram says. “Teaching them how to understand what their data is telling them and what needs to be done in their organisation is the opportunity.”

That means starting with the basics around data literacy, before moving them on to more advanced analytics, and eventually on to AI.

“That midmarket is very competitive, and they want to be able to pick up trends and that little bit of insight to get that competitive edge early enough, because competitive windows are closing much faster than in the old days,” Bertram says.

“And unless they are investing in some of these tools that allow them to pick up what is happening with their business early enough and give them time to react to change, then they are going to go out of business quicker.

“So there is the demand for it, they are very scared about where to start.”

That may be the case, but it seems to be an opportunity that much of the channel is yet to pursue. Even those organisations that are servicing midmarket companies generally do so as an adjunct to their main work with larger organisations.

The D-word

Analytics might seem like a new opportunity for many channel companies. Not to Rod Jacka.

His 17-year-old firm, Panalysis, has provided these services for years. Panalysis was the first Google Analytics partner appointed in Australia, and while its focus remains in the digital space working with enterprise clients, a year ago he signed a relationship with Domo to help clients better work with data from different systems.

Jacka says Domo has proven useful for SME clients, helping them demystify data by presenting easy-to-consume dashboards and alerts that deliver owners what they need to be successful, such as whether they are on track or not. This has been of particular benefit to one of Jacka’s SME clients, the gift hamper company Gourmet Baskets.

“He uses a combination of tools, one of which is [marketing and sales management platform] Infusionsoft, and Xero for his invoicing,” Jacka says. “For him to understand his market and break his market into different stratas, he can’t do that in Infusionsoft easily. And so Domo has allowed him to connect this up and get visibility across each of the platforms he’s used in a single, easy-to digest manner.”

Jacka says one of the secrets to working with smaller clients on data projects is to never talk about data.

“The business owners know what they want to do, but they often don’t know how to do it,” Jacka says. “Data isn’t really what they are talking about, but they need data in order to achieve their goal.

“I actually prefer not to use the word ‘data’. I prefer to use the word ‘evidence’.”

Other organisations that now offer services in the data space often started out somewhere else. Melbourne-based automation and DevOps consultancy Vibrato built its analytics practice 18 months ago through the evolution of its devops consulting business to encompass the concept of dataops.

Vibrato’s chief executive and founder, Peter Gatt, says over time his firm has learned to package up analytics services into fixed-price solutions that are suitable for SMEs. He says smaller thinking is required to help smaller clients.

“With a small and medium business we say, ‘Let’s look at one analytical thing you are trying to ask or answer, and that traditionally reporting could help answer’,” he says. “It is not about bringing in petabytes of data and running Hadoop protocols. We are just going to coordinate the data they have into something that’s logical so they can start to answer questions about their clients and commercialise that data.”

Send in the clouds

In some instances Gatt says engagement with smaller businesses is actually easier, as it is possible to speak directly to the boss or function head, such as the CMO, who owns the actual problem needing to be solved.

When there this is a specific question to be answered through an analytics project, Gatt says Vibrato can deliver a return-on-investment through a proof-of-value in as little as four weeks.

“With data, that’s possible,” Gatt says. “But it really needs to be locked to answering questions, not just playing.”

Vibrato has also established relationships with technology providers such as Hortonworks, and makes use of the Snowflake cloud-based data warehouse tool to help accelerate data flows to make the fast turnaround possible.

Indeed, the migration of analytics tools to the cloud has proven beneficial for a number of channel companies, including Empired.

“I can stand up a Microsoft solution on my credit card and do it really quickly,” says Empired’s national business manager for data insights and integration, Ben Johnson.

“The other change is you used to have to knit all kinds of different tools together – Oracle for database and Business Objects for the front end and IBM for predictive analytics. All of that is blown away because the market is converged. Microsoft has an end-to-end data and AI capability that you can stand up quickly and start getting value straight away.”

However, reducing the barriers to entry from a technology perspective has also had other consequences.

“It’s new and it’s sexy and everyone is a data scientist and everyone is talking about AI,” Johnson says. “The realty is most of them are pretenders, because there has been such an influx of people who are interested but don’t understand the space.”

Are you experienced?

It seems experienced skills remains one of the key attributes that set the successful players apart from Johnson’s pretenders, and Johnson has hired a team of 70 specialists over the past two years to build out the necessary experience.

Jacka also rates staff development as one of his top priorities. He has hired everyone from scientists to mathematicians and artists, and then trained them up on the technology.

“The thing I look for in my team is thinking skills,” Jacka says. “If they have a good problem-solving mindset and aptitude for creative thinking, I like them. But it can take three to six months to get them ready, and I’d argue that it takes 10 years to become an expert.”

Justin Parcell, director of Arq Group business InfoReady, says the requirement to get the right skills meant he and founder Tristan Sternson personally oversaw the hiring of the first 60 or so staff.

Originally the firm was focused on consulting services focused on the information management domain, primarily around IBM environments, but more recently InfoReady has built a competency in AWS and Azure, and three years ago rebranded as a data and analytics organisation, with a greater focus on delivering systems that support operational decisions, rather than for strategic decision making.

He agrees that the shift to the cloud has opened opportunities to service smaller clients.

“As the services that are provided by the cloud platforms become more sophisticated, and as the cost to stand-up those solutions and implements them reduces over time, I think they are going to become more accessible to those smaller companies,” Parcell says.

But while the tools are becoming easier to stand and up work with, he believes that skills remain the limiting factor preventing other organisations from easily following in InfoReady’s footsteps.

“To become a fully fledged data analytics organisation there is a significant barrier to entry,” he says.

 

Domo Partnership

Angela Conn - Monday, August, 13, 2018

Panalysis Domo Partnership

Panalysis is committed to helping clients make better business decisions. As a Certified Domo Channel Partner, we are able to deliver additional value with the world’s best business optimisation platform.

Domo’s mission is to be the operating system for business, digitally connecting all your people, your data and your systems, empowering them to collaborate better, make better decisions and be more efficient, right from their phones. Domo works with many of the world’s leading and most progressive brands across multiple industries including retail, media and entertainment, manufacturing, finance and more.

We’re excited about the future with Domo. We haven’t seen such a transformative tool until now. What we are most excited about is the extent to which we can now help our clients bring so many data sets together (web, marketing,social, operations, sales, customers and product), with the ability to curate the data story that matters most to their businesses. Data democratisation is important, but the data story will focus decision making, avoid misinterpretation and increase efficiency and profits. Together with Domo, we can do exactly that for our clients.” Rod Jacka, Managing Director.

Domo offers you:

  • A single solution for all of your business data and decision making.
  • Rapid set up, cleaner data and faster insights
  • Hundreds of prebuilt connector apps to streamline your existing data sources into one centralised platform
  • Visuals to help you sell your data story
  • Business collaboration within the tool and saves your commentary
  • A seamless mobile experience so you can access and interact with your business data on the run
  • Intuitive notifications via email or text if your key metrics are underperforming, in real time

If you are interested in a platform which brings your people and the data they rely on together in one place, contact Panalysis to arrange a demonstration.

Introducing Google Marketing Platform

Rod Jacka - Monday, July, 09, 2018

Since the introduction of DoubleClick in 1996, changes in technology have meant changes for digital marketers. With more channels, formats and data and an increase in consumer awareness around how they are being marketed to and how their data is being used, there has been a need to provide marketers with new tolls to make it easier to get better results with privacy at the forefront.

To meet these new realities, Google announced Google Marketing Platform at the end of last month.

The platform brings together DoubleClick Digital Marketing and the Google Analytics 360 Suite to aid in the planning, buying, measurement and optimisation of digital media and customer experiences. In one place, Google Marketing Platform.

The platform brings together DoubleClick Digital Marketing and the Google Analytics 360 Suite to aid in the planning, buying, measurement and optimisation of digital media and customer experiences. In one place, Google Marketing Platform.

Google Marketing Platform helps marketers to better understand their customers by offering tools to collaborate and share insights, achieving a customer- first approach to marketing.

 

The Highlights

  • Google products work even better together. For example, the new integration centre helps you to discover and set up valuable connections between products.
  • The platform supports over 100 integrations. You can choose what media you buy, how you buy it and how you measure it.
  • DoubleClick Search is now Search Ads 360
  • Display & Video 360 fuses features from display advertising products and allows you to execute ad campaigns in one place, end to end, improving efficiencies.

 

Find out more about Google Marketing Platform from your Panalysis Contact.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Reference: https://www.blog.google/products/marketingplatform/360/introducing-google-marketing-platform/

 

Symantec SSL Certificates

Rod Jacka - Thursday, February, 22, 2018

Executive Summary

Summary of the Situation

The Chrome team no longer trust previously issued Symantec certificates, and DigiCert have been selected as the new primary provider of SSL certificate infrastructure.

Symantec will maintain their role as an issuer of certificates, but DigiCert will manage the ‘Managed Partner Infrastructure’ on their behalf.

Technically Symantec are now selling certificates with this ‘new’ infrastructure, so certificates purchased from them can be renewed.
However, given the situation we recommend going straight to DigiCert.

April 17th 2018:

Chrome 66 scheduled for release, which removes trust in Symantec-issued certificates issued prior to June 1st 2016

October 23rd 2018:

Chrome 77 is scheduled for release, which removes trust in all ‘old’ Symantec-issued certificates issued on or after June 1st 2016

How to check SSL Certificate Status

Step 1) Visit the website using Chrome

Step 2) Open Developer Tools and refresh

(CTRL+SHIFT+I) ← (letter i, not L) or F12

Step 3) Review the Console

If the SSL certificate in use was issued prior to June 1st 2016, the console will display this message: (M66, must be replaced by mid April)

If the SSL certificate was issued on or after June 1st 2016, the console will display this message: (M70, must be replaced by mid October)

Full Background Information

Google Security Blog – Chrome’s Plan to Distrust Symantec Certificates

This article provides a full overview of the situation.

Key details:

CHEAT SHEET: Apple Analytics vs Google Analytics App Measures

Rod Jacka - Monday, February, 19, 2018

Have you assumed that Apple Analytics and Google Analytics provide very similar app measures? Unaware of some key differences between the two analytics platforms?

We’ve compiled a helpful cheat sheet for you, providing a side by side comparison to aid your understanding and maximise your app measures.

METRICAPPLE ANALYTICSGOOGLE ANALYTICS
App DownloadsApp Units are the number of first-time app downloads made on the App Store (from iOS 8 onwards).  Updates and redownloads onto other devices are not included in this numberNew Users is the number of first launches, or the number of sessions in which the app is first opened on a device, it excludes users who have opened the app previously during the selected period
CampaignsThe attribution window for campaigns is 24 hours.  If a customer downloads your app for the first time within 24 hours of using your campaign link, you will see this counted as an App Unit (app download).  Attribution goes to last click, so if the user clicks on more than one campaign link, only the most recently clicked on will be attributed to the App Unit.  These settings are not adjustableThe attribution window for first-open is 30 days.  The attribution window for any subsequent in-app conversions is 180 days.  These settings are not adjustable
ImpressionsThe number of times your app was viewed in the Featured, Categories, Top Charts, and Search sections of the App Store. Includes Product Page ViewsImpression data is not available in Google Analytics.  However, in the Play Store, you will be able to see Play Store (Organic) who are the unique users who visited your app’s store listing by browsing or searching on the Play Store app
RetentionRetention is the usage of your app over time. The number of devices still active with at least one session on a date during the retention periodThe retention cohort report describes a set of users (a cohort) who started using your app at the same time (such as on the same day, or during the same week). This report illustrates how well the app retains users
SessionsSessions are counted when the app has been used for at least two seconds. If the app is in the background and is later used again, that counts as another session. Totals are based on app users who agree to share their data with you.  There is no current documentation on the length of a session as is available in GASessions are counted when the user is actively engaged with the app.  Google Analytics groups hits (page views and events) that are received within 30 minutes of one another into the same session
SourcesCurrently, there are 4 different types of sources that are recorded in Apple Analytics.  These are App Referrer, App Store Browse, App Store Search and Web ReferrerThis is not measured by default, it requires tracking to be added to the url under utm_source.  The source in GA describes where the user arrived from (website name, social network name, email list name etc.)

GDPR is Coming and You Need to Pay Attention

Rod Jacka - Thursday, February, 15, 2018

Key Takeaways:

  • You need to be aware of the EU GDPR
  • Your company is potentially impacted by this even though you are located in Australia
  • The potential fines for breaches are huge
  • You need to think privacy first

 

Europe has historically been far more privacy conscious than the US, Australia and many other regions. The European Union (EU) has developed new legislation called the General Data Protection Regulation (GDPR) that has the potential for significant impacts on companies across the world, including Australia.

The GDPR legislation is due to come into effect on May 25, 2018. This is similar to the privacy legislation in Australia but the potential fines are far more significant with a maximum fine of $20 million dollars or 4% of global turnover whichever is the greater.

This legislation provides very strict rules about how data is treated when it impacts citizens of the European union and includes rights such as:

  1. Right of Access
  2. Right to Rectification
  3. Right to Erasure, and
  4. Right to Data Portability

You might think that this only is relevant for businesses located in Europe. Unfortunately, this is incorrect. The legislation has significant potential to impact Australian businesses as the legislation states that it applies wherever the entity offers goods and services to EU residents; or monitors EU residents’ behaviour.

From the page at https://www.gdpreu.org/the-regulation/who-must-comply/ the following is offered as guidance to whether a business must comply with the GDPR.

May be insufficient evidence

  • The firm’s website is accessible to EU residents
  • The firm’s email or other contact details is accessible to EU residents
  • The firm is located in a non-EU state that speaks the same language as an EU state

May be sufficient evidence

  • The firm markets its goods and services in the same language as that which is generally used in an EU member state
  • The firm lists prices in EU member state currencies (the Euro, British pound sterling, Swiss franc, etc.)
  • The firm cites EU customers or users

Based on this, the key risk areas for Australian businesses are where they offer information in languages from the EU countries, listing pricing in Euros, Swiss Francs, etc. or where customer testimonials or similar referrer to EU residents.

A typical example of where a company may unwittingly be exposed to the requirement to be compliant under GDPR is the use of local currency on their websites.

 

Additionally the explicit statement that your company ships to EU countries may also mean that you need to comply with the GDPR.

 

One way that you can quickly check to see how many users you have to your website from EU countries is to use the Google Analytics geographic reports.

 

A lesser known potential risk is that companies can initiate action on other companies under the GDPR. This opens the risk that competitors can potentially use this legislation as a way of causing damage to your business.

 

What should you do?

Australia already has a Privacy Act [1]that provides some of these rights already however the EU GDPR has additional rights that are not covered under the existing Australian Privacy Act.

Australian Privacy Act GDPR
Right of Access Y Y
Right to Rectification Y Y
Right to Erasure N Y
Right to Data Portability N Y

 

At a high level there are two key areas that Australian businesses will need to work on to be compliant with the GDPR requirements. These are the right to erasure and the right to data portability.

If you are already compliant under the Privacy Act then you may already have the processes in place to satisfy the requirements of the GDPR. However, if an EU citizen requests that you supply all of their data so that they can take it to another provider then this may present some difficulties to your company. Also the right to be forgotten and to have their customer data erased can provide some significant challenges to your business.

At the very least your company should document the data it is collecting on its customers and to implement processes to meet the GDPR obligations. This will require conducting audits of the data that is collected, why it is collected, where it is stored and how it should be treated.

Data dictionaries, documentation and governance frameworks are now far more important to Australian businesses and the time to act is now.

If you would like to discuss how the GDPR potentially impacts your company or would like an assessment of your digital analytics data please contact us.

For further details on the GDPR please visit https://www.gdpreu.org/

[1] https://www.oaic.gov.au/privacy-law/rights-and-responsibilities

Getting Started with Case Statements In Domo

Damien Smith - Tuesday, January, 09, 2018

My previous article ‘Introduction to Beast Mode in Domo’ provides a high level view of Beast Modes and why you would use them. The examples were basic calculations of profit and margin for the whole dataset.

Things get a little more complicated where we need to return results from only some of the data. Case Statements are used for this purpose.

Case Statement Structure

I don’t have a background in databases or SQL so when I first started using Domo I was struggling with case statements – it just wasn’t clicking for me.

It all came together when I thought of the case statement as a filter on the data and then doing something with the resulting rows.

The case statement has the following structure:

CASE WHEN <some filter conditions> THEN <do something> END

Example

We need a pie chart to always show the split of shipping mode from last year without updating date filters each year.

This beast mode says that when the year of the order date equals the year of the current date – 1 (ie. filter on last year), then return the data in the Ship Mode column:

The beast mode becomes the name of a new virtual column which only shows results for where the order date was 1 year ago (2017 at the time of writing).

Using the above beast mode, this pie chart shows the shipping mode composition for last year

The end result:

Insights, please. Actionable ones!

Rod Jacka - Monday, December, 11, 2017

When you find a true insight, it can make your head spin. But, will your head spin in a different direction if the insight is found in Australia than if it is found in the United States? On this episode, Rod Jacka from Panalysis joins the crew for a balanced discussion (northern AND southern hemispheres) about how the phrase “actionable insights” should turn the stomach of any right-thinking analyst. More importantly, the gang discusses the need for clarity around insights — both definitionally and expectations-wise — and share their favourite techniques for getting that clarity.

Introduction to Beast Mode in Domo

Damien Smith -

This will probably be a familiar scenario: you need to create some charts based on a dataset which almost has what you need, but not quite.

The fundamental data is there but you need extra columns for profit and margin but really don’t want to wait for a new extract. This is where you would use Domo’s Beast Mode.

Beast Mode in Domo is the same as a calculated field – it’s a way to create a new column of data based on the existing data.

As a simple example say we have this dataset:

A new Beast Mode for profit would look like this:

Which produces the new virtual column for Profit:

A Beast Mode for margin looks like this:

And produces the new Margin column:

 

The Beast Modes can then be used in a chart:

Why use a Beast Mode over an ETL Transform?

The above example is a simple one where adding the calculated columns in an ETL transform (such as MagicETL) would be trivial, but there are a number of advantages to working with Beast Modes:

  1. Beast Modes dynamically calculate the values. You will come across situations where the values need to be calculated on the fly based on time range or dynamic filters. Baking these calculated values into the dataset would be troublesome or simply impossible.
  2. Beast Modes don’t mess with your dataset. Change control of a transform needs to be managed carefully to ensure accuracy of the resulting dataset. Once a transform has been ‘signed off’ and accepted as correct it should not be touched again without testing and QAing the changes. This is an important but laborious process.
  3. Beast Modes are only visible in the card they’re required for. Even though you can save Beast Modes to a dataset we recommend you don’t, unless it will be used consistently across multiple cards. Saving the Beast Modes in the cards reduces the clutter of dimensions and metrics when creating new cards.

Can Beast Modes be used instead of ETLs?

No. There are many things that a Beast Mode can’t do which must be completed in an ETL. For example:

  1. Combining metrics from multiple datasets into a single output dataset. Cards can only show the columns from a single dataset.
  2. Changing column types (eg from text to date).
  3. Ranking functions (eg ranking values as position 1, 2, 3).
  4. Many, many other functions.

What Beast Mode functions are available?

If you are familiar with SQL then Beast Mode won’t be much of a leap. If not, don’t worry as it’s quite simple, however the simplicity can sometimes be a challenge when you are trying to achieve a complex outcome.

The full list of functions can be found here: https://knowledge.domo.com/?cid=beastmodereference

Top tip: Take some time to skim read each one to be aware of what’s available even if you don’t know how to use them all.

This is your toolbox. If you’re building a house and need to cut some wood then you’ll have a very difficult time if you don’t know that such a thing as a saw exists. Know your tools.

Getting the Most from Enhanced Ecommerce in Google Analytics

Rod Jacka - Friday, November, 17, 2017

Why report on only the purchase values of your website, when you can track and report on every stage and interaction that leads up to it?

With Google Analytics Enhanced Ecommerce you can do just that! Here are our top analytics management tips if you’re using Google Analytics as your primary analytics tool.

  1. Standard vs Enhanced. If you’re currently using Standard Ecommerce tracking you’re missing out on a huge amount of valuable data that can improve your bottom line. There is work required to get this implemented but the results are worth the effort and cost.To see the difference visit panalysis.com/whyEE
    To get started visit panalysis.com/goEE
  2. Data quality: As the old saying goes, Garbage In, Garbage Out. There are many things that can impact the quality of the data in Google Analytics. Make sure you’re tracking what you need, and not what you don’t. Check you’re clear of the common set-up mistakes panalysis.com/GIGO
  1. Tag and track your marketing campaigns: The single biggest issue that we see with how people use Google Analytics is that they don’t track their marketing campaigns effectively. Implement campaign tags on all your campaigns and do so in a structured way.
  2. Set up internal promotions and coupon tracking: Understand how effective your on-site promotion strategies are in driving sales. Google Analytics Enhanced Ecommerce allows you to track sales from promotional tiles on your site as well as coupon redemption.
  3. Make reporting make sense: Map your reports to your shopping cart process and merchandising structure. Tailor your funnel paths to match your shopping paths, product impressions, and set your reports up to follow this flow. This will give you a greater understanding of your customers’ shopping behaviour, checkout behaviour, product engagement and sales performance
  4. Data goes both ways: Analysing your Ecommerce transactional data and marketing data only tells half of the story. Consider integrating related external system data and setting up custom data fields. This will give you a powerful data set that you can use for real decision making and competitive advantage.
  5. Create baseline measures: Before you start to try to improve your metrics you should create baseline measures so that you can understand how much your actions changed the results.
  6. Start optimising: There is no point just collecting data, you need to start doing something with it. Create an optimisation plan and then start working on it.

Whether you’re using Shopify, Magento, Woocommerce or any other Ecommerce platform you’ll want to understand what’s really happening in your business. Remember to always cross check and validate your data regularly as you make changes to your site.

Google Analytics isn’t your primary analytics system? It is still useful for cross checking and validating activity data as your site evolves.

     

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