The three trends driving marketing analytics in 2018

marketing trends

In this era of data-driven everything, the need for high-quality marketing analytics has never been greater.

Yet for many companies, marketing analytics still consists of a weekly report and perhaps a dashboard or two.

More forward-thinking organisations, however, have been pushing ahead with new analytics tools and processes. To find out more about these trends in marketing analytics, Econsultancy recently invited industry expert David Sanderson, CEO, Nugit to present at Digital Outlook 2018 in Singapore. To an audience of over 400 marketers, David spelled out what will be driving marketing analytics in 2018 and how marketers can keep up.

Before we start with the summary, we’d just like to let you know that Econsultancy is holding an Advanced Mastering Analytics course in Singapore on April 5th, 2018. You can find out more and book your spot here.

1) Marketing analysts will need to use many new data sources

Traditionally, business decisions in many organisations were powered by marketing analytics which relied on big, centralized-managed data servers or data warehouses. According to David, though, things have been changing recently and now companies find that analysts also need to ferret out data stored in many ‘mini’ data warehouses.

In addition to the usual internal data repositories, marketing analysts also need to pull data from dozens of separate systems including:

  • Google Analytics
  • SEO platform
  • Salesforce or other CRM
  • Email service provider
  • Major media platforms: Facebook, Twitter, AdWords
  • Chat applications

Combined, these data sources will provide better insights for marketing and sales than internal systems on their own and they will help the business drive consumer interest, optimize pricing, and deliver an improved customer experience.

So, according to David, analysts must now do more than just analyse. They must also identify where important data resides, determine what needs to be extracted and devise a strategy for using new data sources to drive business decisions.

2) Artificial intelligence (AI) will be essential for analytics

David also noted that the speed of data coming into the organisation has now increased to the extent that it is no longer possible for human analysts to process it all.

To help, a number of firms have sprung up which offer marketing analytics with baked-in artificial intelligence (AI). These systems use machine learning and other AI techniques to help analysts find patterns in customer data, elicit recommendations for optimising performance, and allow non-professionals to access complicated analytics using simple language.

For example, Hyper Anna, a venture-backed marketing provider of ‘machine intelligence for marketers’, takes in company data and returns ‘high-impact use cases’. This means that marketing data such as customer interactions, financial performance, and supplier activities can be uploaded and Hyper Anna provides information about cross-sell and upsell opportunities, revenue forecasting, and supply chain management information.

Another firm, Datorama offers ‘AI-powered marketing intelligence’ which makes it easy for marketers to unify data across systems and access powerful analytics using natural language.  David pointed out that Datorama is now integrated with Amazon’s Alexa and offers voice-activated marketing analytics.

3) Analysts will become storytellers

While the analyst toolbox traditionally consisted of skills such as SQL, business analysis, and Excel, analysts in 2018 will be expected to do much more than crunch data and produce reports.

With the new data sources and AI tools described above, analysts will be expected to:

  • Obtain data from non-traditional sources,
  • Clean data with programming languages such as Python,
  • ‘Polish’ the data using data visualization tools and create attractive charts and graphs, and
  • Transform data into easy-to-understand stories which help non-analysts understand emerging trends and opportunities

Simply creating a dashboard and sending out a weekly report will not be enough. Like all marketers, analysts in 2018 will have to focus more on their customers – the people in the organisation who need to extract meaning from all of the data now available so that they can improve business performance.

A word of thanks

Econsultancy would like to thank David Sanderson, CEO Nugit for his presentation about what we can all expect for marketing analytics in 2018.

We’d also like to thank everyone who attended on the day. We hope you gained valuable insights from the programme and that we will see you at future Econsultancy events!

NOTE: This article was written by Jeff Rajeck, and was published on www.econsultancy.com. You can read the full article HERE.

What Big Data Tells us in the Marketplace

what big data tells us

As a business owner, do you know what big data tells us?

It’s frightening that most folks don’t know how to answer this question. What you market and how you market it is not the most important thing you do.

This statement IS true if you have no idea who your ideal customer is.

Reading and tracking the metrics of your social marketing are important, don’t get me wrong. However, it all starts at the very beginning.

This means that you go back to WHY you chose your niche market. Who is your ideal customer? You can only build your marketing plan once you know who they are.

Is there one major tactic you can use to keep you ahead?

Maybe, but the one principle you can build on is putting the customer first. When you do so, you’ll be able to then find the marketing techniques that work the best.

Today, I am going to share with you what big data is and what big data tells us so that we can approach our marketing campaign with laser-focused targeting.

What Big Data Tells Us in the Era of Computers

Did you know that computers play an important role in processing data and telling us everything we need to know about our customers?

Data is a great way to track human behavior, and computers are helping us use systems and processes that do just that. They process important information about how humans function in the world and their buying decisions.

This is especially true when it comes to retail.

Retail data gives us a ton of important information, and it gives us a good look at how humans react to commercials, certain types of advertising and why they make a specific decision in the end to buy.

Consider that a company looks at their quarterly earnings, and ultimately they know whether or not they performed up to par.

Following a tough economy, it’s no surprise that so many companies are spending their dough on retail data and human behavior. They want to know what makes you tick, and what gets you to pull that “buying trigger”.

If you can capture data on every single action a human being takes, you can also predict exactly what a customer is going to do next.

You can find out what they are doing next, tomorrow, or even possibly in the next five years. Scary eh?

The thing is, this data isn’t stalking people, but it tells us a lot about what people do and why. Why do you buy a specific type of towel? Why do you drink a certain type of drink at a certain time of day?

What big data tells us is that human beings are predictable, and they are predictable enough that you can plan out your business for the next year.

What if you could craft our copywriting, capture pages, and websites just right, to set it up for a total customer experience?

You can.

What Big Data Tells Us Through Social Media

Social media is a great experiment full of case studies.

This is why social media is now one of the foremost tools online marketers use, along with small and medium sized companies.

What we can learn most about data through social media is the habits of our customers online and how it relates to us marketing to them in a more effective way.

Pixel, a phenomenal tool on Facebook allows us to watch what other pages a customer is viewing once they have left our page.

This is great news, because it means that we can see more about their personal decisions online. This has opened up the door for more streamlined Facebook marketing.

Big data can tell us a lot, but we need to sift through it often as e-commerce changes to serve our customers better. If you knew where your customer was going to look next, would you want to know that information?

What big data tells us is critical for our marketing campaigns.