The B2B marketing leaders will be spending more money on technology than the CIO in 2017. Sure they may already spend a lot, but the interesting question here is: will they now finally be able to identify the revenue?
It was not long ago when CMO’s were perfectly ok with having more and more new technology tools. The problem came when they were forced to maintain the tools and, also to measure the performance of those tools in order to prove that they were still needed.
While each platform may include its own reporting tools, in an omnichannel world, having so many partial views of the truth makes little sense.
Many business users and decision makers can’t see the forest for the trees when it comes to the current analytics environment. How will they manage then in an Analytics of Things of world with 6.4 billion connected devices? Are CMO’s prepared?
According to a recent study on The State of Marketing Analytics by VentureBeat, “Analytics are key to showing value, yet the market is huge and fragmented.” Customers are no longer using a single channel to buy yet only 60% of marketers create integrated strategies.
Probably the most painful source to measure is social media. It is painful because there’s no way that investors will accept engagement metrics such as impressions or likes as revenue. It is also painful because the CMO is being pushed by market analysts to invest more and more budget on social media.
Social media spending is expected to climb to a 20.9% share of marketing budgets in 5 years even though analytics is not yet fully integrated or embedded according to a recent CMO Survey.
ROI of social media in the form of adding new revenue sources, enhancing revenue sources and increasing revenues is more pronounced among companies with a more mature data-driven culture. The graph below shows where competitive advantage has been achieved as a result of data-driven marketing by stage of development according to Forbes.
What’s worse for the laggards is that their immature analytics culture is resulting in the lowest profitability – they even don’t know often which analytics platforms they are paying for, according to the same research.
“There is no substitute for hard work,” said Thomas Edison. In order to identify the ROI of social media marketing, we will go through the hard work by going through the requirements for your social media data below, including:
- Why you need integration and democratization of data in the cloud, including social media data
- Why you need self-service advanced and predictive analytics for your campaigns
- Why agility is so important when it comes to marketing analytics
- Why integrated reporting and insights should be easy to access by any marketer or business user
Integration and democratization of data in the cloud, including social media data
This is not just useful to get a single view of the truth. Working in an environment where each platform’s reporting is separate from the others, is not possible to calculate ROI of social media marketing. You may find a way to calculate the revenue of a Paid Per Click campaign in LinkedIn for example, but this is a very narrow view of what social media marketing is about.
The first step to identify the real revenue of social media should be to integrate all disparate data sources in the cloud. They should be integrated, because that way you will be able to cross reference information, discover the real 360º customer view and the actual ROI. Also, it should be integrated in the cloud specifically so other business users can access and self-service the final insights.
Some people may think they have a 360º customer view when they integrate Google Analytics and Salesforce to calculate the ROI of a paid campaign in Google Adwords. But they are still far from that view. According to Think with Google, for instance, customers in most industries in US click on a paid ad long after they were engaged in social. That means that a percentage of the ROI of the Pay Per Click campaign should be attributed to social to be accurate.
What if instead of making assumptions you start to track which channel is the first, then which is next, and which is the latest? You can do this with tools like Piwik or Eloqua Insights because they track all different devices from which the customer is visiting your website as well as specific URLs they land on, and order the events by date.
While this is fine if you have less than 200 sessions per day on your website, if you have more than that you will quickly understand why big data is more than just hype!
Trust me, if you had the time to explore, analyze and export using Piwik or Eloqua Insights you would really know what patience means. With big data, even if you just want to use a selected small part of it, you need columnar database technology like the one used by OpenText™ Big Data Analytics.
Having your data sources integrated at the start and managed by IT is fine, but when it comes to data audits, data cleansing and data enrichment you had better expect this to be self-service.
B2B companies need to know as much as they can about the companies they market to and 75% of B2B marketers say that accurate data is critical for achieving their goals but lack of data on Industry, Revenue, and Employees is a problem in up to 87% of the examples.
Bad data affects not just marketing but also sales, according to Forrester, executive buyers find that 77% of the sales people they meet don’t understand their issues and where they can help. As a result a lot of CMOs are taking the initiative to start profiling and creating more targeted leads so that sales don’t have this problem.
Self-service advanced and predictive analytics for marketing campaigns
According to a recent study by MDG Advertising, B2B organizations that utilize predictive analytics are 2x more likely to exceed their annual marketing ROI goal.
The research offers interesting reasons why 89% of B2B organizations have predictive analytics on their roadmap.
According to VentureBeat there are 3 main reasons why marketers aren’t that advanced in their analytical approaches – including skill gaps around data science. Easy-to-use tools can make it easier to run reports, but without a real understanding of data-driven approaches, the final report may not be accurate enough.
Predictive lead scoring, for instance, can yield significant ROI and 90% of large organizations will have a Chief Data Officer or CDO by 2019. Meanwhile CMOs are not inactive and 55% of B2B organizations are already hiring for marketing analytics roles.
Success in social media is not as easy as being 30 years old. You know that you will be 29 years old for 12 months and then it will automatically change to 30. This is easy to predict, but it is not scalable to social media. In terms of social media you need to go deeper than the surface to measure, for example, if it is worth having 30 social media accounts or maybe 10. You need to measure if it is worth having 30 blog articles or maybe 300.
You will want to calculate if “Channel A” is worthwhile because it generated 300 conversions from unqualified leads or not. You may want to go further and identify which of the qualified leads bought “Product A” and “Product C” but haven’t yet bought “Product B”. Do you want better segmentations and profiles of those, so you can create a custom cross-selling campaign, based on information that you can get from LinkedIn, for instance? If so, you will need to go further than data visualization.
Companies need advanced analytics to identify ROI. This is what will give you the insight on the ROI of your social media, but more than it could ensure success in the current digital era.
You will find the following ad-hoc & pre-built tools at OpenText Big Data Analytics:
- Venn Diagram: Are you tired of reaching the wrong people? Smarter companies are reporting benefits doing data mining to target advanced segmentations and the most appropriate people with marketing material that resonates with them. Note that segmentations are based on data mining, but can be created by drag and drop of the database objects in the left column.
- Profile: Are you still re-marketing to visitors who landed on your website by mistake? Our drag and drop, easy-to-use tool is needed by marketing in the current customer-centric culture. B2B marketing goals for predictive analytics span the customer funnel including customer retention, customer lifetime value, customer effectiveness right up to customer acquisition – so having a customer profile is a must-have to begin.
- Association Rules: What if you could identify which users are likely to abandon with sentiment analysis of their activity in social media and help-desks – so you can reduce churn with a loyalty campaign? Would that help the ROI of your social media?
Companies plan to increase spend on marketing analytics, but many will select the wrong capabilities or be unable to use them properly. Harvard Business Review alerts to this point “marketing analytics can have a substantial impact on a company’s growth, but companies must figure out how to make the best use of it”.
Why agility is so important when it comes to marketing analytics
You already know that advanced and predictive analytics is not new, if you think about how financial services has been using it. What’s really new is how easy analysis can be created as self-service now.
In the real world, only 20% of organizations are able to deploy a model into operational use in less than 2 weeks according to TDWI, so don’t forget to ask for self-service and real-time advanced analytics. You will be happy that your analytics platform technology includes a columnar database when you get to this point.
Why integrated reporting and insights should be easy to access by any marketer or business user
3 out of 4 marketers can’t measure and report on the contribution of their programs to the business. Isn’t that scary? To know the customer and how to deliver relevant data is a key business differentiator. Marketing analytics tools need to be more than a nicely displayed report, they need to allow decision makers to interact with the information according to McKinsey & Company.
There’s a lot that has been written about the opportunities of using big data in supply chain and retail companies, and specifically the social media capabilities to reach their audiences. The retail analytics market is estimated to grow from 2.2 billion to 5.1 billion in 5 years but difficulty in sharing customer analytics is ranked as a top challenge by the Industry.
Social media is a smart way to connect a customer with a specific local store, right? Instagram includes stats of impressions, reach, clicks and follower activity for businesses. There are a few tools with powerful capabilities to personalize, share and embedded HTML5 data visualizations available, but OpenText™ Information Hub is the only one that is tied to advanced and predictive analytics.
9 out of 10 sales and marketing professionals report the greatest departmental interest is in being able to access analytics within front-office applications and OpenText Information Hub is ranked as the top vendor in the latest Embedded Business Intelligence Market Study by analyst Howard Dresner – not without reason.
Don’t forget to ask for an analytics platform that is perfectly fine to be scaled to unlimited users.
Turn your social data into strategy, then gold
Predictive analytics not only applies to what will happen next quarter, but also to what the user may want to find right now. Google doesn’t wait for you to make association rules that have probably helped you a few times – they make their big data work for millions of users in real-time.
Now think about your company and one of your prospects sharing your content on social media or email. Do you create a campaign to track and nurture these actions? How do you react if a user won’t complete a form more than once? What do you do when one of your prospects is searching on your site having landed from a social media post about “Product A”? Are you able to identify that “Product C” will be the more likely purchase?
There are musicians unhappy about piracy, but there are others tracking, mining and getting revenue from social data. Getting these insights on revenue before running new omnichannel campaigns will provide one voice communication, essential for a successful omnichannel strategy. What is also important: this will help with better data-driven decisions and greater return on investment of your social media budget.
86% of companies that deployed predictive analytics for two or more years saw increased marketing return on investment according to Forbes.
Download the Research “Operationalizing and Embedding Analytics for Action” from TDWI
The report notes that operationalizing and embedding analytics requires more than static dashboards that are updated once a day, or less. It requires integrating actionable insights into your applications, devices and databases. Download the report here.