Table of Contents
show
Big data has become a crucial growth enabler by empowering companies with deep insights into the internal business processes along with the competitors and market. This exponential demand for data has led to the mushrooming of startups focusing on acquiring, analysing and building innovative products on top of big data. We have also witnessed a rise in the number of acquisition of big data startups by the bigger tech companies.
Some of the notable acquisitions in this context are listed down.
Microsoft acquires Big Data analytics startup Metanautix
Microsoft acquired big data analytics Startup Metanautix back in 2015 to tackle one of the biggest challenges in data analytics – bringing data together for powerful analytics and discovering growth opportunities through intelligent automation. The enormous amount of information created by the company had to be used to power their data-driven strategies and activities. The technology of Metanautix could break the boundaries and connect the “data supply chain” regardless of the size, location or type of the organization’s data, which attracted Microsoft towards them.
SAP acquires Altiscale
Enterprise software provider SAP acquired Altiscale, a big data startup with a unique offering- a cloud based version of Hadoop. The solution can be highly useful for storing, processing and analysing various types of data. This acquisition was aimed at enhancing the cloud software portfolio of SAP, which will give them a clear upper hand in the battle with their equally mighty competitors, like Microsoft and IBM. This also hints at the increasing popularity of cloud based big data services.
Apple acquires Tuplejump
Tech giant Apple has been on a big data company buying spree. After Perceptio and Turi, Apple recently acquired another big data company called Tuplejump. Apple is known to be secretive about their purpose or plans with the companies they acquire. However, Tuplejump was working on an open source project that would use machine learning techniques and analytics on huge amounts of data in real time. Considering how this could give a competitive edge to Apple in the business intelligence front, we can safely assume that this was what Apple was seeking.
Why big companies are acquiring big data startups
Big data can be as powerful as a diamond blade. With the right tools and technology to acquire, analyse and derive valuable insights from it, companies can easily get ahead of their competitors within no time. Bigger companies are well aware of this fact. When a new startup comes up with technological advancement in big data and machine learning, none of the big guys want their competitors getting hold of it. This, along with the advantage of having the best tools to handle data, makes acquiring such startups a lucrative thing to do for the bigger companies. Here are the key reasons behind such acquisitions.
Identifying new markets
Spotting new opportunities is one of the biggest advantages of having a solid big data analytics stack. This is something that big companies are always looking out for and data can aid them in discovering such opportunities. Data can give clear insights on the firmographic, demographic and behavioural profile of customers. When a high number of customers who don’t fit their buyer personas are found, it can indicate a new market to be targeted. This can only be identified with robust big data technologies which can either be built or bought.
Exploring new markets can sometimes be like drilling a dry well, but not with big data. Data can show companies where their customers are and where they aren’t. Having this foresight is tremendously helpful and gives a unique competitive edge. By investing the time and efforts in new ventures that are sure to give returns, companies can also cut down on their wastage and thus enjoy a very high operational efficiency.
Enabling Revenue Performance Marketing
Marketing can often turn into a black box. Although a lot of money goes into it and comes out, many companies still can’t figure out how this black box operates. By using a marketing ROI tracking mechanism using machine learning and data analytics, companies stand a chance to identify what works and what not with marketing. With a system like this implemented, companies can assign a value to each action taken by their leads and track/predict marketing campaign outcomes. This is what many companies are looking to achieve with their big data startup acquisitions.
Generating lead Intelligence
Every lead that has ever come in contact with a company would have left some data footprints. This data can be stored and analysed to identify a pattern among the highly profitable leads, enabling the companies to match them with the newer incoming leads to prioritise them accordingly. This prioritization helps them allocate more time and efforts for the high potential leads rather than spending it equally among all the leads. To take lead intelligence further, cohort analysis can be used on this data to derive different cohorts (groups) and different personas can be assigned to each cohort. This will help the company in seeing patterns across the life-cycle of a customer rather than individually slicing across all customers blindly.
Providing better customer experience and service
Providing a better service and customer experience is one of the top priorities of every successful business. This can sometimes be a tough task if the customer base is wide. Big data can be of great help here, as it can give them a comprehensive profile for each of their customers. Anticipating their needs and discovering the issues faced by them can go a long way when it comes to providing a better service.
More data is better data
All companies are acquiring more data than ever, and the bigger ones are even acquiring the companies that can help them with big data. This trend doesn’t seem to be fading anytime soon. Since data is one of the best competitive advantages for companies in this digital era, acquiring and making use of it will stay among the top priorities of companies, big and small alike.
