Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it. ~ Dan Ariely
The above quote never fails to generate a smile but I don’t think it holds true. Not for big enterprises. Not anymore. Under the leadership of Chief Data officers, most big companies are bringing together technology, talent and data assets (new and existing) in a way never seen before and Big Data & Analytics is now an integral part of their enterprise strategy.
Small Businesses on the other hand are a different story. Having talked to both new parents and small businesses, here is my analogy:
Big Data for Small Business is like post baby sex- nobody really expects to you to do it, you have convinced yourself it is highly overrated, and while it would be a ‘nice to have’, after a long tiring day, it’s not your priority. ~ Gazal Kapoor
If you are a new parent, you will change your mind.
If on the other hand, you are a small business, I am here to change your mind about Big Data. Whether you own a start-up or a mature localised business, here are my top 5 reasons on why analytics and big data should be your priority.
1. Know your customer: Your customer is more than the wallet that keeps your business running. Your customer is a person that has hopes, dreams, challenges and struggles just like you. Big data analytics will help you know your customer and personalise your offerings.
2. Map your customer experience: Whatever your product offering is, you provide your customer an experience and you need to understand it. Your customer has an opinion of you and they use it to influence. Big data analytics will help you understand why people choose you over your competitors, help you map their experience at different touch points and understand the voice of your customer.
3. Changing customer and macro dynamics: As a small business owner you are most likely busy on the dance floor. The world around you is changing very fast and no matter how much fun dancing is, you need to step on the balcony from time to time. Big data analytics will help you be at the fore front of trends that are changing your industry and help you drive a return based strategy.
4. Know your Competitors: Big data analytics not only means generating information from your own data assets, it also means tapping into sources of information outside your hold to tell you more about who else is competing with you for your customer’s share of wallet. And if your competitors think they are not big enough for big data, big data analytics will help you get ahead of them.
5. Get Social: Big data analytics will help you integrate social media into your marketing to increase the return on your marketing spend.
If you think you are too small a business and don’t even have the data, the truth is, If you have run your business for a couple of years, have a functional website to interact with a customer and a Facebook page, you have a treasure trove of data already that you are doing nothing with. You can start to dip your toe into big data by looking at public domain – Customer Search Trends from Google, Tweets in Twitter and Facebook Public Posts or even Government and Public Data Sources.
Where is the time, you say.
I hear you on that. One of the biggest challenges a small business face is operations consume almost all their time. The other challenge is budget.
The good news is there are many analytics companies that can partner with you and do all of the above on a shoe string budget. A great analytics partner will not only tap into public and social domain, they will help you create a rich repository of data by making small tweaks in your data systems. They will work closely with you to use the right tools to capture and analyse relevant data and make the most of it. In fact, Small Businesses are in a better position than their bigger counterparts to generate returns from Big Data investments because of scale, agility and nimbleness.
Don’t wait. Treat Big Data Analytics as a ‘must have’ for your small business and see the difference it makes.
In my next post, I will talk about how to choose an analytics partner.
Author Profile: Gazal Kapoor is an analytics professional with experience across domains, geographies and industries. She describes a career in analytics as a passionate arranged marriage but that doesn’t prevent her from flirting with writing from time to time.
Gazal Kapoor works full time in Sydney and is a guest blogger for Convergytics.
Posted in Blogs,
John (name changed) is a Marketer for a leading apparel eTailer based in New York. John joined his current company recently and is struggling to make sense of the reports in his Inbox. The #s and findings in the reports just don’t add up. While their analytics vendor sends out 10-15 reports each week, no one on his team uses these reports. No one on the team was even aware of who requested so many reports. The vendor blames the poor data quality for the unreliable numbers and the poor usage. John wonders how he can improve the quality of his analytics projects and if there is a solution.
This is a typical scenario encountered by many a marketer / e-marketer. The root-cause of these are common mistakes that analytics teams (internal and external) make. What are these common but critical mistakes and how can you make sure you avoid them?
1. Unused Reports / Unimplemented Models = No Perceived Value
Is your team / vendor doing work that is eventually not getting used?
You should first inventory the analytics projects and identify the key stakeholders for each. Identify team members who will benefit most from each project. Get these team members to review the work and use it to make decisions. Motivate them to inform you if they feel that they may not have a need for it (now rather than later).
You should do a quarterly exercise to cut redundant work by sitting with your team and your vendors . This exercise will ensure only useful projects remain. A review before a major project launch will ensure you are investing only in useful projects.
As a vendor, you need to take ownership of tracking usage of each project that you work on. Most BI Tools today come with usage tracking features. XL and other reports sent using email can use email/link tracking tools to measure usage. Share the findings with your project sponsor to showcase the impact of your work. A dramatic solution to an unused report is to pull the plug on it for 1-2 weeks and see if anybody complains. If no one does, you can indeed pull the plug on those reports.
Is your team following due procedure when it comes to QA of the reports / analytics projects that are going out?
Are there a standard set of checks required before any report / analytics recommendation / model goes out? Is the process documentation detailed enough to avoid errors due to personnel changes? Are there many QA check-points within a project? E.g. Ensure that the # of customers in your modeling data-set on is in the ball park.
QA is an important ingredient for an error-free deliverable in any analytics project. You need to confirm advanced analytics projects and presentations make business sense. You also need to ensure that the model is a good model.
Who do you blame as an analytics team for poor data?
The Data Team (if you were not part of it) or just the stars (if you were). Data will never be perfect. You need to budget enough time in a project for data treatment and call out the assumptions made.
When many data sources are available, you must use the newer, more reliable and less error prone one. It could also so happen that the data was clean for some channels and no so clean for some other channels (e.g. Online). In that case, adopting a hybrid strategy might work better. A first step is to gain access to all key data sources and compare the key metrics (KPIs) across them.
A digital website audit by a digital analytics vendor would be a good first step. This would help identify mistakes around usability, analytics implementation and reporting. You must repeat this audit at least 2-4 times a year to ensure any new changes made do not impact the site and the data. You might need more frequent audits for a website that undergoes frequent changes.
Does your report tell a story, a single story?
Getting a deliverable ready to present / share with your client is only the first step. Making sure that the #s and recommendations make sense is important. It is easy to get lost in the numbers and lose sight of the reason for the request. The “So-what” or the “5-Whys” technique will help get to the bottom of what the numbers mean. They will also help make recommendations to the client to take certain actions.
You must remember “correlation is not causality” and “averages are misleading” when making recommendations. You might need to drill-down further to see if the recommendations you are making are valid.
Is your project making an impact?
You feel that you are doing some great work. But, is it making an impact by driving decisions. Is your model implemented in market? If your answer is “No”, you might not have given it enough thought at the start of the project. You must invest time at the start of a project to ensure that you are solving the right problem. You must also ensure that you are structuring the problem in the right way. A well-structured problem helps more than a cutting-edge tool or even a sophisticated technique.
You must ensure that any report includes recommendations based on your interpretation of data. You must also encourage users to provide feedback on these recommendations. Starting a conversation intrigues more stakeholders to use and get value from the reports. Even if you get corrected on your findings, it is likely to be because of some information that you missed as a team. You should request for the extra information and use it to improve the recommendations. More information could include campaign calendars, creatives, market dynamics or product launch schedules.
Author Profile: Randhir Hebbar is an entrepreneur and one of the founders of Convergytics – Asia’s leading analytics brand in 2015-16 (as per UK based Global Brands Magazine). He heads the Digital Analytics and BI Practice at Convergytics and also is the Account Lead for several key accounts. He has consulted with dozens of leading Fortune 500 Retail, e-Tail, Technology, Telecom and Media Companies over the past 15 years and as an Analytics Leader within the organizations that he has been a part off, has encouraged team members to strive to avoid some of the mistakes listed in the article.
Posted in Blogs, Tagged analytics project, Convergytics, mistakes in analytics, Web Analytics,Bollywood is an industry that has a value of Rs. 138 billion and is expected to reach Rs.1661 billion by 2017 (FICCI-KPMG report). And if this is not impressive enough, the industry has produced 1.6 billion movies so far which is 4 times the number of Hollywood movies produced till date. Indians have grown up with Bollywood (popular name of Indian Film Industry), watching all the emotions on the screen. One way or another, it has rubbed off on us to an extent that the tickets sold in India are 2.6 billion, nearly twice of that sold in Hollywood.
With a turnover of 2.23 Billion USD and overall marketing spend of roughly 50% per film, the movie business in India is one of the highest spenders in marketing promotion. Considering the size of the industry, it becomes imperative to ask- “Is Marketing being done here the right way? Can we improve the efficiency of spends?”
A decade ago, most of this promotion was straightforward with a limited number of channels to spread the marketing message to a less distracted target audience. With the dawn of the social media and ubiquity of smartphones, reaching an attention deficit audience is now the biggest challenge for production houses and their marketing teams. Which channels to focus on? How to customize the message for each channel? How to allocate spends across channels? These are some of the questions that challenge today’s movie business.
The future is NOW
The last decade has not only seen an increase in the diversity of devices on which entertainment is consumed, but also in the profile of the audience that is now getting used to custom content.
As digital devices adorn new avatars (e.g. wearables) it will become important to understand what type of content is optimal for these devices and how to customize the content as per insights from the audience’s digital profile. Netflix has already started profiling audiences to inform content creation. As the launch campaigns for new movies go omni-channel they will enhance their targeting to incorporate these different data streams to generate a custom genre fit.
At Convergytics, we believe this Future is Now and we have been doing some interesting work in this space. For more information, please reach out to [email protected] OR [email protected].
This article was first published on LinkedIn by Sanjeev Mishra (CEO, Convergytics) and was reposted here with minor modifications.
Posted in Blogs, Marketing, Tagged bollywood movie marketing, Convergytics, entertainment analytics, marketing effectiveness, Web Analytics,If you’re not 100% thrilled about all that time you’ve been plugging away on analyzing customer data, you are not alone. The big struggles we see marketers from industries of all types obsessing over are ALWAYS related to the details of measuring the success of their efforts. They have questions like:
Convergytics recently got listed among the Top 10 companies by Edupristine. Below is the Top 10 list as per the leading Education & Training Portal
