How analytics solutions are going to change.
Marketers constantly use insights delivered by their analytics tools to look into the future of their businesses. But how about the future of analytics tools themselves?
Today, analytics has become an umbrella term that spans a wide range of actions – basically anything that delivers meaningful insights from data. With a virtually unlimited quantity of data and data sources, analytics providers face an important challenge: How to deliver services and products capable of handling the Herculean task of getting actionable insights from data – even at the enterprise level.
Analytics has evolved to reflect the breadth of data being collected. Indeed, analytics is only meaningful when used in tandem with a more specific term – web analytics, customer analytics, marketing analytics, predictive analytics, big data streaming analytics, performance analytics and so on.
That said, all of these analytics branches center, in one way or another, on understanding user behavior. In line with current market needs and trends, understanding the customer behavior and activating those insights requires three steps.
- Collecting data via SDKs, third-party services and internal services such as CRM, ERP, etc., to combine online and offline data in one platform. This lets analysts and marketers drill down into data with desired metrics and dimensions to reach the right insights.
- Answering the question of “What do we do with this data?” This involves building segments to manage data and conduct predictive analyses with that managed data.
- Activating this data with marketing triggers. You have segments and you can trigger your third-party services and combine the results of those marketing activities with your current data to do accurate analyses.
For instance, let’s say you have a clothing shop with a new men’s collection. You can easily create a segment of people who bought men’s clothing before. Then you can trigger your email service to send relevant recommendations and offers. According to the results of the email campaign, you can create a retargeting list for the people who opened your targeting email. Whenever they buy an item from that particular collection, you send that data to your CRM and label those customers as a loyal buyers.
Online actions are getting more and more agile, and you are supposed to be able to act on your data with one click – without losing time to code and connect services.
This is the backdrop we used to determine seven predictions for analytics market. Let’s dive in.
1. User-centricity will be the “must-have” for product-focused analytics solutions
Analytics solutions have evolved to become a lot more than data visualization tools. Businesses collect and drill down into data to create meaningful insights for their corporate decisions and marketing actions. Maximizing profit depends on understanding the users, personalizing your activities and segmenting according to interests or personas.
This is why analytics solutions have become user-centric, allowing users to drill down customer data with precise dimensions and metrics. But this user-centricity trend has only just begun. The ways in which marketers and analysts can build use-centric profiles – merging behaviors, purchases and intentions across devices and over long periods of time – will continue to evolve and improve.
Channel-centric, device-centric – it will all be replaced by user-centric.
2. Digital Intelligence will transform into Customer Intelligence
Digital Intelligence is one of the biggest differentiation points for analytics providers. It is a broad term, but its scope can be boiled down to
- “Data Management and Availability,” such as anonymous data association, data portability and predictive analytics
- “Reporting and Analysis Functionality,” such as industry-specific reporting and benchmarks, path analysis and mobile apps
- “Integration Support,” such as application programming interfaces (APIs), post-implementation managed services and product performance.
Conforming to the new market needs and demands, Digital Intelligence started to transform into Customer Intelligence. The most significant difference between the two is that Customer Intelligence is better suited to incorporate CRM and ERP connections, and allows you to enhance your data with other third-party service connections. This unleashes insights from data and ultimately enables data activation by triggering third-party service actions.
3. Third-party data connections and audience stream will be embedded features in customer analytics solutions
Nowadays, businesses gather data from a huge (and growing) list of different platforms. You have email data in your email tool, e-commerce data in your shop system, support data in your ticket system. The list goes on. Analytics providers need to facilitate the merging of all this data into one platform, and enable businesses to stream this data to other services directly from their analytics solutions.
According to these market requirements, audience stream is becoming more and more essential every day. Audience stream has three main functionalities. The first is pulling data from third-party service connections. The second is pushing data to third-party service connections. And the third is syncing your data with third-party solutions.
What does syncing data mean? For example, say you have a segment of customers who bounced from the process of buying men’s apparel in the last three weeks. You want to synchronize this list with your retargeting list.
The segment is dynamically growing, but also some customers are exiting from this segment after a number of weeks. A data sync enables you to feed that data to your third-party services, and remove them from the list to optimize marketing costs and efforts.
Examples like this abound. Marketers have to be able to execute these kinds of actions without any dependence on technical skills or third-party solutions. That is why it will become a market standard in analytics solutions.
4. Activating data with marketing actions will be part of analytics more than marketing automation tools
Marketers are using marketing automation tools to run their automated SaaS funnels. But all these marketing automation solutions are CRM-focused, and they offer their own marketing services independent from the marketing services already implemented. This results in extra marketing costs and disorganized data.
Analytics solutions will solve this problem in the near future by allowing their customers to combine their online and offline data with better CRM, ERP and third-party data connections. Analytics solutions will also enable custom marketing actions – or trigger users’ third-party services for email, push notifications, advertisement, etc. – with one click.
5. Cross-device tracking and custom track domains will define the new data quality standards of the market
Optimizing operational and marketing costs is extremely dependent on the quality of data that businesses possess. Why is data quality so crucial? Let’s examine this topic with two hot technologies: custom track domains and cross-device tracking.
As you are probably aware, ad blockers are becoming more and more popular every day. According to research, businesses lose 13% of their overall visitor data as a result of ad blocker usage – which also corresponds to 40% of overall Millennial data. That’s why custom track domains – which enable companies to collect better data by setting analytics cookies from within their own domains – will be so vital. They fill in that missing data.
Another hot concept is cross-device tracking. It is easy when people connect to your system from different devices with the same unique identifier. But how about unifying the device data within a big pool of device connections?
Advanced cross-device tracking will let businesses match their data by using extensive device pools consisting of all available unique identifiers and device information, as well as their mappings. As a result of cross-device tracking, businesses will be able to unify their visitor data between 13% – 40%, according to Webtrekk research.
These two technologies directly impact the marketing and operational costs of your business by merging data. Therefore, they will be an integral part of analytics solutions in the near future.
6. Data privacy and data ownership will become a must-have in vendor selection criteria
Data privacy and handling of private data have always been topics of concern. Recent news suggests, however, that it will continue to be a primary focus and will be even more strictly regulated than it already is.
Industrial espionage, governmental regulations and the enomrous penalties attached to those regulations are causing some angst. We can explore data privacy by breaking it down to the following subjects: “importance of data privacy for businesses” and “data privacy regulations for businesses.”
Cybercrime has grown rapidly in the last five years. One of the biggest weapons in a cybercriminal’s arsenal is PII, or personally identifiable information.
Businesses have started to engage in preventative measures to keep their data and, by extension, their customers safe. It is crucial yet not sufficient if only the corporations take responsibility and are held liable. Usually, a lot of third-party services and cloud technologies are involved in the mix; the data has to be shared with other parties in one form or another.
Tech giants such as Microsoft are acknowledging the gravity of this situation and taking steps toward new offerings to tackle cybercrime. For instance, Microsoft recently released Azure Stack, which offers similar levels of functionality and services to Azure, but which lives in on-premises servers to meet the demands of customers and requirements of data privacy. Analytics solutions are one of the most important and prominent services that businesses utilize. This is why data privacy will be more essential in the near future.
And then there are regulatory changes. The European Commission has already adopted data privacy regulations that will go live in May 2018. These regulations, spelled out in the General Data Privacy Regulation and the corresponding ePrivacy Regulation, will place much stricter requirements on how companies can collect and use data. The European Commission is not seeking to outlaw analytics, but they are introducing handcuffs that will limit the ways in which analytics solutions function, and the corresponding data is used.
7. Predictions, machine learning, AI and smart notifications are the next destination of the market
Predictions and machine learning enable actions that are virtually impossible to accomplish even with very large teams at your disposal.
There are lots of different ways to use machine learning algorithms in analytics tools. Those algorithms allow analytics customers to do predictive analytics, compare predictions and actuals, determine influencing metrics for specific goals, understand anomalies and give insights to customers to maximize their profits – just to name a few use cases.
Machine learning definitely has the potential to unleash all the capabilities of analytics tools in not-so-distant future.
Artificial Intelligence has recently become the focal point of a lot of debate and news coverage. For instance, Facebook AI was shut down after it started to create its own language. Additionally, a Chinese AI project started to criticize the political systembefore being shut down as well. Those were instances that clearly demonstrate the vast potential of Artificial Intelligence – and the risks involved.
Will AI have an impact on the analytics market soon? Quite frankly, there is no definitive answer to that question yet. But it sure looks like it will, especially in the Business Intelligence market. AI could be the ultimate consultant for business and marketing decision making.
In conclusion, the big data and analytics market is transforming rapidly. According to customer feedbacks, market research and market trends, we tried to present some our predictions for you. If you have any questions or comments about these predictions, please do not hesitate to contact me.