Investing money in big data can be a huge gamble. Avoid these common mistakes when implementing a big data program.
Big data is hot. Really hot.
In fact, many suspect that using big data as a marketing tool itself should only go up for the considerable future.
However, investing money in big data can be a huge gamble, and sometimes a huge failure.
Customer service is the name of the game, but if businesses manage big data inappropriately, they can end up doing more damage to themselves and their customers than good.
Here are a few of the biggest fails businesses make with big data, so you can avoid them:
1. Choosing the Wrong Model
Big data must be thought of as an Olympic-sized swimming pool full of pennies. On each of these pennies is a person’s Facebook post detailing the things they like, but each penny only has one of this person’s posts written on it.
The next lists the next person’s post, and so on, and so on. With this in mind, it becomes quite clear that diving to the bottom and finding the right collection of pennies for your business is just about impossible, with the wrong methods.
Many businesses look to analysts and Hadoop to solve this problem, and then call it a day, but this is wrong. Each business and their needs are unique, and this makes it important to consult with professionals to decide the proper big data model to sort through your data and find the assets you need.
Many small businesses will benefit from using a big data in the cloud vendor over using an on-premises option. Where your data is currently stored, and how much it would cost in productivity to move that data should all be taken into account when setting up big data infrastructure.
2. Too Much Focus on Big Data
With the ability to predict what customers want before they want them, businesses focus a great deal of funds and resources on making big data the best it can be, while disregarding other elements of their customer service.
Drawing in customers and getting them to buy is only half of the game. It’s important to make yourself available and accommodating to passing customers who want to learn more without the benefit of an ad campaign.
Allocating funds away from call services, secretaries, and web developers can see you bringing in some customers, but completely driving away others.
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3. Targeting the Wrong Customers
It can be highly tempting to reach into the magic hat of big data and pull out as much as you can; after all, if you can reach unlimited customers, isn’t this better?
However, it’s impossible to be everything to everyone, and it’s much more important to focus on your niche rather than getting mixed up in several others.
Many businesses make this mistake, but to avoid it yourself, it’s important to know who your ideal client is. Are they female, in their 30s, making $60,000 a year, and own a home?
Then this is the person you should gather information on rather than getting mixed up with others, otherwise you'll find yourself with too much information to actually decipher and act on.
4. Over-Complicating Things
Big data does give you extreme amounts of information that you can store on flash storage, but not all of it is useful. Like a kid in a candy shop, some businesses get so thrilled with the data they’ve gathered that they forget more is actually less.
Instead of gathering tons of data that must be siphoned through, narrow down your efforts and only collect data on your ideal customer, so you can see exactly what they want in relation to your product.
When businesses dive into big data, most of them expect serious results. However, in doing so, they forget to focus marketing plans in other directions while big data builds up steam.
You won’t see results immediately and giving up on traditional methods in the meantime will see you losing the momentum you’ve built up until now, losing the interest of buyers when you could be cashing in. Don’t expect big data to solve all your problems. It’s a tool, not a miracle.
Big data is undoubtedly a fantastic asset for businesses, but it’s important to remember that it’s designed and used for customer service. If it fails to accomplish this task, then it’s rendered entirely useless, costing you incredible amounts of money.
By looking to the mistakes of others and seeing how to avoid them, you can dodge the fluff and create a method of utilizing all big data has to offer you, without any of the failure.