The term big data is thrown around like a college frisbee. From interview to boardroom marketers are asking about big data and for good reason.
Big data is a term used to describe the massive volumes of data that inundate the modern business 24/7, 365 days a year.
Using powerful algorithms, computers, and a healthy serving of data science, companies analyze this data and draw meaningful insights that help them make decisions, set up strategies, and basically do everything better.
It’s still early days for big data. The term first made it into the lexicon in the early 2000s, before we had 2 billion mobile phones, impending IOTs and virtual reality, behavioral targeting data, programmatic everything, and you get the point. We are collecting more data than ever, and it’s difficult to see the trend slowing.
Let’s consider what the future of marketing has in store for big data.
Future of Marketing Big Data: 10 Companies on The Front Lines
Finding companies on the front lines of big data isn’t difficult. There are thousands of startups eager to make a name for themselves with innovative products SaaS, self-service platforms, API and SDK plugins, you name it and there is a tech company measuring it.
The problem is so many companies smack big data labels on their products when they aren’t crunching the numbers. Everything sounds impressive with the processing power of PCs, but I want to showcase 10 companies that really handle data-heavy processing to get insights that others would overlook.
Mixpanel is a business analytics service and company that tracks actual user interaction on a website or mobile app. That is an important distinction. It isn’t guessing what users are doing based on clicks, impression, and other engagement metrics, Mixpanel knows what people are doing the second they do it.
Mixpanel was launched in 2009 and quickly got a leg up on its competitors by focusing on mobile. In 2014, the company said that they analyzed over 34 billion actions every month. That sounds like pretty big data to me.
You can use it for basics like A/B testing but instead of tracking the users click-through-rate on version A or B you can see how they continued to interact with the site, how they got to the site, and just go beyond what most analytics software is offering.
Simple dashboard and clear displays of complex data means that you don’t need to be a data scientist to use Mixpanel.
Conversion Logic is a cross-channel measurement platform that combines cloud analytics and machine learning. The result is a nifty analytics tool that takes sophisticated data science and turns it into actionable insight.
Gathering marketing analytics across channels like smart Tv, Apple watches, and Wi-Fi cars is no small task. They are called impersonal channels, because you can’t identify users with simple cookies or by writing code into apps, like with a smartphone.
Conversion Logic is a SaaS analytics service that provides a view across all touch points. This saves marketers from needing to master several tools, for each platform, and makes it easier to compare data across platforms and determine was is and isn’t working.
The customer’s experience doesn’t end once the sale is made. Customer advocacy is vital for driving further sales and exposure. We all know that repeat business is worth 7xs more than the original sale and driving up LTV of your customers increases how much you can spend on customer acquisition.
Wootric are calling themselves the net promotor score platform for boosting customer happiness. They aim to address the problems that companies face with evaluating and collecting data. Customer feedback data can be overwhelming. Wootric breaks down feedback and arranges It according to sentiment.
To increase response rates, it simplifies user feedback with automation by displaying a simple rate 1 – 10 system, inside the web browser or mobile app. This doesn’t disrupt the user’s experience with surveys or take up resources sending emails.
Two clicks. Rate out of ten and explain your score. The case studies on the Wootric’s site show customer response rates in the 80% – 90%. That’s kind of a big deal.
HyperScience wasn’t made exclusively for marketing. It has wide-reaching applications that place it at the future of all kinds of industries. I chose to include it because it alludes to the larger automation trend and the role that big data will play.
HyperScience is a startup that’s aiming to automate data entry and all the mundane tasks that take up unnecessary resources.
For the marketing organization that processes large volumes of data and pays someone a salary to spend their day arranging data into excel spreadsheets this is a welcome disruption.
The machine learning algorithm learns over time, and the goal is that it can handle bigger tasks or just do the same ones quicker.
Mobile analytics have proven to be a tough nut to crack. MightySignal has a big data approach to gathering insight.
It works by crawling the web and looking for buying signals and leads. Founders Jason Lew and Shane Wey envision the software being used to help software companies push their SaaS offerings.
It can also provide information about what SDKs are being used by an IOS or Android app. It crawls through source code to get this information and complicated process made so simple a CMO can find new opportunities with a few clicks.
Node.io is a behavioral targeting startup that uses big data to help companies better target the people buying their product. It has crawled through endless online data to create more than half a billion user and company profiles. With AI and data science, Node.io can analyze all these profiles and identify who you’ve had the most success selling to.
Data is power. Aligning a marketing strategy with the people who are going to convert is marketing 101. Node.io isn’t doing anything new. It is just doing it better.
There are account based marketing applications and the AI’s data-based approach to qualifying results in better leads.
Virtual reality is quickly becoming a serious platform for marketers. A study by TechCrunch predicts that AR/VR could be a $108 billion industry by 2021.
Companies are going to want to get in on that. Be it native advertising with virtual billboards or just finding a way to build VR content, there will be investment.
CognitiveVR is one of many companies racing to provide analytics services so that marketers can measure engagement and calculate ROI.
Already supporting all the popular headsets, CognitiveVR gathers user’s data by tracking VR sessions and polling user voice feedback.
Anodot is one of the better big data startups to ever do it. Their software can monitor marketing campaigns to report on clicks and bids for ad campaigns.
It can monitor conversions and on sight behavior for your websites and ecommerce, and it can identify bugs, track software and report on outages that affect the user’s experience.
Anodot does a little bit of everything and handles a lot of data to do it.
David Drai, the CEO and co-founder, told Forbes “With big data, the challenge is how to find the right insight, or in many of our use cases, the right business incidents in the data,” To that end Anodot has a general-purpose Ai that doesn’t just solve problems it finds them in the data.
Based on Apache Kafka, a messaging platform which became a lot more, Confluent is a platform used to stream data and process it in real time. I am not super techy, and I’ve always just understood it as Apache Kafka with extra features. If you aren’t happy with this definition, I recommend you do your own research or risk being led astray by me.
These are some of the ways that organizations are processing and handling the data coming in. It’s a mess.
Apache Kafka and, by extension, confluent make it much easier to manage all this data. Confluent improves Kafka by making it easier to manage clusters, ensure that streams are secure, and expand its integration capacity.
Search-driven analytics for humans is an exciting enough title to make most marketer’s ears pivot. ThoughtSpot aimed to make analyzing company data as easy as searching on Google. Without training, anyone in an organization can retrieve actionable data and insight.
It’s a compelling pitch. While big data has irrefutable advantages, it has been a real hassle. CMOs had to expand their skill set and vocabulary, marketing companies had to hire mathematicians and engineers to make sense of all the numbers, and companies spent thousands training everyone.
There aren’t many concrete numbers, but ThoughtSpot has some impressive testimonials from major companies. The overall trend is that it does what it promises and makes BI software a pleasant experience for sales and marketing teams.