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The power of big data is only becoming more accessible and powerful with each passing day. With a focus on the numbers, you can use your marketing-decision making skills even further by taking advantage when algorithms make recommendations or provide insights into what might work best for different circumstances!
Data is the foundation of today’s business world. Each day, organizations get to interact with data concerning customers, vendors, security, and even employees. Sadly, 73% of it goes to waste. Even worse, the remaining 27% of data which is analyzed doesn't always result in quality insights. A good chunk of companies still struggles in identifying the best data to draw their insights.
Data science is the process of gathering, organizing and analyzing data in order for it be used by someone who may not know how.
It can also mean using computer programs or algorithms with a goal; this could include things like building models that predict the likelihood something will happen.
Developing a culture that supports data analysis and embracing modern-day practices can have many benefits.
Luckily, it is those businesses that can separate the wheat from the chaff in their data mines that can harness the power that lies in data analytics. When used wisely, data can be a driver of change in your business, both by unveiling opportunities and pointing out problematic areas. This trickles down to how you collect and analyze your data.
A growth hacker is someone who can use their analytics and marketing skills to create a successful business. They do this by obtaining varying sets of knowledge about analyzing data, understanding human behavior patterns, applying design thinking principles in order to come up with new strategies for businesses that will lead them towards success.
There's a saying: data is the new gold. And, it goes without saying that your business is going to be disrupted by the hottest data and analytics trends. Here is how data can revolutionize your business:
#1 Create a Great Customer Journey
What is a customer journey?
A customer journey map is a visual representation of the sequence of events and actions customers take when they interact with your business. Most importantly, it shows how you can engage customers in a way that will lead to increased sales and loyalty. A customer journey will help both marketers and designers understand how customers move through their site or app in order to achieve their goals. It's important for marketing teams to accurately predict where customers might need help, while UX designers must know when and where to add value points in order to influence user thinking and behavior.
Why use Customer Journey Mapping?
Customer Journey Mapping allows you to see gaps in the experience your users are having, identify missed opportunities, make smarter decisions about what changes should be made, and ultimately influence trust, loyalty, and revenue.
The growth hacking methodology is all about cultivating a culture of experimentation where marketing teams are constantly experimenting and learning new ways to impact your entire funnel. Simulate customers' journey in order for you test the results with real people, collect feedback from them so that we can evolve together. Web analytics (Or app analytics) will help you map your customer journey and improve it along the way.
Data is invaluable in identifying the pain point of your target audience, and in defining them in the first place. When used to create a buyer persona, it can help you align your product and service specifications with what the market demands. In fact, data analytics can unearth new and disruptive opportunities in your industry that are right under your nose.
For instance, learning the networking gap of the dating world led to the development of dating sites. By gathering data on the opinion of customers, you can not only make your business reliable and convenient to them but also increase your market share.
Ideally, you should concentrate on online reviews and customer feedback to identify what your business needs to improve.
Additionally, aspects such as optimizing your business for an online audience can help you tap into a new demographic of consumers.
The higher the quality of data you can collect, the easier it will be to understand the typical customer and cater for their needs.
#2 Cybersecurity
Cybersecurity is the name for security when it comes to computers and networks. Computers and networks often rely on software and hardware that contains errors, or bugs . If these errors enable a third party (e.g., any person not directly authorized) to do things they're not supposed to be allowed to, we call this a computer security vulnerability.
Companies operating online a lot know the importance of cybersecurity. Cyber threats have become a norm in today's world to the point that investors and customers are only interested in doing business with companies with healthy security postures. You want to protect your data as your business grows. Third-party stakeholders aside, experiencing a cyber-attack can be detrimental to your business both in terms of reputation and daily operations. Luckily, building a strong cybersecurity posture can be supported by great data analytics practices.
You will regularly need to know the chances of a cyber-attack happening and the impact that it can have on your business. More importantly, you need to assess the effectiveness of the different cybersecurity strategies in protecting your data and their projected ROI. Once you invest in security tools, it is wise also to have a team of professional analyze the alerts they generate. The power to differentiate between false positive and positive alerts can be an x-factor in detecting security risks.
With excellent analytics practices in place, predictive analysis becomes easy too as you begin to identify patterns in your historical security data. Lastly, data analytics in security can help avoid PR nightmares.
There are many benefits of cloud computing for businesses and improve your cyber security is one of them. If you have data as a cushion, you can calm key stakeholders in times of a crisis.
#3 Talent Acquisition and Retention
As the AI, data analytics, machine learning or Internet of Things are becoming more and more popular, it is important for recruiters to catch up with this trend. Instead of applying traditional ways of recruitment, they need to consider data analytics.
It's not surprising that some people are sceptical about using big data in hiring. Their main fear is that reliance on technology will take away human touch from recruitment process. This way they might forget about essential elements like empathy and personal skills when choosing candidates who fit well with the company ethos and culture, which can make or break a business. However, many employers see potential advantages of adopting advanced technologies influencing new generation demands for work-life balance, flexible working conditions and gaining access to new talent pools beyond geographical boundaries. Big data has the power to affect radical change in the recruitment industry.
There are many ways how data analytics can be used for hiring process improvement.
Here is an example of how it works: if you want new employees to match your company vision, values and culture - you need to know what these factors are. Then, list all the keywords that reflect your business strategy and use them as search criteria for finding new employees on LinkedIn, Indeed or social media platforms.
For instance, a CEO of a consulting firm told us that she knew exactly what kind of person was needed in her company when they wanted to grow their team in a successful way. As a result, they have been able to apply this knowledge when using big data tools in recruitment - which allowed them to find people with experience in the industry who would fit well into the company culture.
Even if you are not planning to make radical changes to your hiring process, it is worth taking a look at big data opportunities for recruitment because it gives an opportunity to save time and money on advertising vacancies that will be overlooked by potential employees. You can tell which types of jobs are trending on LinkedIn, UpWork, Indeed.... If you want to hire sales representatives, try searching for people who have written "sales", "business development" etc. in their profiles. This way you will see how many new people join these platforms daily and get a chance to contact them before they get a job offer from another company.
What's more, it's important not to rely solely on big data tools. Sometimes, they can give you false information because there are so many factors to take into account when recruiting people.
Therefore, it is always worth to consider the human factor in recruitment process for finding staff with certain psychological traits that can contribute to success of your company. At the same time, you should have a clear vision of what characteristics your business needs and let this guide your search for new employees. Using both approaches - one based on technology and another on intuition - will help you find best talents who are needed in the modern business world.
It is more expensive to attract talent than to keep current employees. It becomes even more costly if you are looking for nothing short of quality talent. Different jobs call for a customized approach and finding someone whose skills rhymes with both business operations and customer expectations can be invaluable.
Furthermore, building a strong workforce can cement your businesses' image in the public's eye. Data science will help you redefining business processes.
Well, attracting the right talent starts with understanding what to look for. Data analytics can help assess the atmosphere of the current job market in comparison to your unfilled job positions. It becomes even more beneficial in talent retention.
For instance, offering a great work-life balance can help retain millennials who crave building a life outside the workplace. As the Gen Z group of employees enters the workplace, understanding the data about what makes them tick can be pivotal. By embracing data analytics to understand the different employee demographics, you can refine your employee scheduling, rewarding, and engagement practices to resonate with your workforce.
#4 Gaining a Competitive Edge
The world of business is changing, and in order not fall behind startups need to be innovative. Growth hacking strategies will help them do just that! Maintaining an informative tone while still maintaining the authoritative voice can make your article seem more professional than others with less detail or information overload - which may lead readers down paths where they're easily convinced into buying something from you.
Growth hacking is an exciting, new concept that has grown in popularity over the last few years. Combining aspects of Product Marketing and Analytics with traditional advertising strategies to increase a company's user-base through innovative means such as paid social media ads, email copywriting, conversion rate optimization, advanced data analysis or SEO optimization -- a growth hacker can significantly impact online success rates for their clients!
Cognitive computing systems are revolutionizing the way we think and interact with technology. The system can learn on its own, recognize images or words in real time and predict outcomes of future events based off past actions - all without human input! Cognitively-powered artificial intelligence also has potential uses far beyond what many people might imagine today which means there will be a lot more opportunities to reap benefits from this exciting new development for everyone.
Data Science is the marriage of mathematics, statistics and computer science. The goal? To create an algorithm that solves problems with data in a meaningful way - be it by predicting trends or understanding what makes people tick!
When we look at a few of the most successful companies in the world, one thing that becomes increasingly clear is how they used growth hacking strategies to turn their ideas into reality and achieve success.
Price wars can quickly happen in the business world. One business tries to lower its prices to push another one out of business, only for the competition to do the same. However, this archaic form of competition often results with one business' death and the other barely managing to remain profitable.
Data can help you remain relevant and build a competitive edge without using such an approach. It helps unveil details such as who your competition is targeting, who they are not, and how to outsmart them. The more you can understand your competition, the better your market domination strategies can become.
With enough emphasis on data, you can identify loopholes in the current market and give rise to disruptive innovations. When trying to be competitive, data can also help differentiate hype from wise investments through both assessing ROI and identifying patterns.
Even if you're on a bootstrapped budget, you now can get and analyze your competitors' data in 4 easy steps.
Implementing advanced data analysis, AI (Artificial Intelligence), ML (Machine Learning) and DL (Deep Learning) to your business models and processes will help you stand out from the crowd. It will give you a competitive advance and help you attain marketing goals.
#5 Lean Management
Having a lean management approach or applying the lean startup methodology to your business can help you gather crucial feedback about your products, your users and your target audience. By launching your MVP (Minimum Viable Product) fast, you will be able to get important data in order to optimize your product and growth hacking strategy accordingly. This will help your business get rapid growth in your industry.
Waste can be quite detrimental to your customer journey. For instance, having long lead times can make customers quite impatient. Additionally, it results in unnecessary expenses during times of limited resources. In fact, in the world of risk management, investing in the wrong security tools can leave critical areas of your business vulnerable despite having maxed out your budget.
Data analytics helps to identify such wasteful parts of your business. You always want to have a data driven decision making approach and mindset.
Remember that lean management is not a one-time investment, and you will continuously need to update your practices to eliminate waste. Lean management can be a solution for reducing product prices without sacrificing profitability.
The trick lies in collecting enough data to paint a picture of your wasteful business operations. Additionally, you will also have to implement strong change management practices to ensure that employees can adjust to tweaks in your daily activities with little friction.
#6 Vendor Management
Vendor management is the practice of maintaining a current, accurate list of approved suppliers and distributors under contract with your organization. Vendor management helps you maintain sufficient inventory levels to ensure that orders are fulfilled properly. It also helps protect your business by limiting new business relationships to those that have been thoroughly vetted.
Your business is only as good as your vendors.
Applying the growth hacking process to your vendor management strategy can do wonders. Having vendors who delay in deliveries and offer subpar products can be the death of your business.
With enough data, you can easily compare vendors and identify who will provide the best quality for your business.
This trickles to the pricing of the vendors. For instance, two cloud vendors might price their product in the same way but have gapping differences in what they offer. Data can help identify this. On the other hand, you might also need to combine vendor services to enjoy optimal product pricing, security, and functionality.
In most cases, identifying the right way to mix such vendor services can be tricky without access to enough data. No matter the situation, the goal should be to get the most bang for your buck.
#7 Demand Management
To remain relevant, your daily operations need to be aligned with the ebbs and flows of demand. A good example would be a restaurant during the offseason. When fewer customers are coming in, the management needs to support its current workforce despite the drop in cash flows. Once the peak season arrives, the business also needs to improve the effectiveness of the workforce while attending to customers.
With both historical and forecasted user data, you can quickly gauge your current and future demand landscape.
You can draw quality insights from it, such as outsourcing tasks, hiring temporary employees, or even upgrading your existing operations. More importantly, it can be easy to predict when customers are unhappy and turn things around.
Thanks to data science and big data analytics, you will be able to improve many important KPIs (Key Performance Indicators) from CAC (Customer Acquisition Cost), CLV or CLTV (Customer Lifetime Value), RoaS (Return on Ad Spend) and many key metrics that will help you reach your business and marketing objectives.
Industrial marketing management is a very important part of business. Industrial marketing management is a field that helps companies and organizations to find their audience. It helps to shape your company's image and promote it through various channels, such as web design or social media posts.
The Power of Optimizing Data Usage
The growth hacker understands that innovation and creative thinking are crucial for finding new ways to bring in business, but there's more than just creativity behind their success. The key lies in the mindset of a marketing scientist - one who knows how important ROI (return on investment) is when it comes time get results!
Your data analytics efforts will only be as good as the quality of your data and the ease of access. Make it your goal to transform, merge, cleanse, and standardize data to increase its usefulness to the decision maker. Ideally, you should establish rules and policies concerning data management on how your staff can use and store the collected data.
These policies should include things that are allowed and forbidden when interacting with the data. Your staff should also understand the best practices for indexing the stored data to increase the efficiency of your databases.
Since there are ways for storing semi-structured and unstructured data in this day and age, there should be no excuse for failing to store transactional, behavioral, and security data. Building an accountability culture can be a sure way to increase the effectiveness of data analysis and collection. It will eliminate negligence among your workforce.
Scale Your Data Management Strategies as the Business Grows
Data driven decision making is key nowadays. As your business grows, yesterday's data management practices will not suffice in upholding tomorrow's standards. For instance, you will require more space to store customer, security, and even operational data after growth. On the other hand, your current security tools might need to be customized to incorporate any new data protection needs that arise.
More importantly, you will have to concentrate more on data security as you look to improve your security practices to reduce the chances of data theft. In return, you can avoid costly business disasters. Your scalability moves should be addressed in advance before purchasing data management tools to make any future transitions smooth.
Otherwise, you might have to completely revamp your entire system and purchase new tools to cater for the changes. Other than the extra costs, the time it takes to move data around from your current systems to new ones can be unpredictable. Losing critical data in the process can also be quite straightforward. Ideally, you should identify the best method for scaling your data needs between upward or outward scaling.
Upward Vs. Outward Scaling
Upward Scaling
Both terms will typically refer to the use of servers among other data center or cloud resources.
With upward scaling (vertical), you will need to improve the hardware capabilities of your current servers.
You or your cloud vendor could increase the memory and even processing power of the existing servers to help deal with any data management deficits created by business growth.
This method helps save cash and time that could have otherwise been used in investing in entirely new hardware. However, the technique has a glass ceiling, and there is only so much you can do to increase the capacity of your data management system.
Scaling Out
Scaling out- or horizontal scaling- deals with adding new hardware among other elements to support the current system. For instance, you can add a complementary data storage server to the current one. In the process, you will divide the burden of handling your ever-expanding data lake among both systems.
This solution is often a long term one as you can add new data management systems to support your current ones. Of course, it might be a tad tough to transition from using a single system in data management to using a clustered one. The tools and applications you choose for data analytics should be compatible enough with both types of scaling to make room for future changes in your business.
When Should You Scale?
If you start hearing complaints from the various departments about data access, it might be too late to begin scaling. Remember, your storage location will store analytical and operational data. As such, a single stall in the retrieval of data could be detrimental to your customer services. When employees struggle to access data, your internal operations will also be impaired. If you start hearing complaints from the various departments about data access, it might be too late to begin scaling.
The trick lies in learning to anticipate such changes in data management. You should be aware of the boundaries of functionality that your current data systems provide you. On the other hand, concentrating on log analysis among other preventative maintenance practices can help you identify problems with your system's uptime as they unfold.
The same mentality should apply when identifying the best time to scale down. If business declines, you will need to use less of your current data management systems, which makes paying for them counterintuitive. In case you are in a volatile industry, using cloud systems in data analytics can keep you prepared for any unexpected scalability challenges.
So, how to use data to grow your business? Final thoughts about growth hacking data analysis?
The world of data science is an exciting and evolving one. With the right use of big data analysis, you can completely reshape your company. There are so many opportunities for those who can see them, but it takes something extra special to stand out in this crowd. The world of data science is a diverse and ever-changing one. It's important for those working in this field to constantly research new trends within the industry, so they can stay up on all their updated knowledge about how things work now versus when we first started using computers over 40 years ago!
Thanks to a data-driven approach, you can grow your sales. In today's world, data is pretty much everywhere and this is probably the most valuable thing on the planet. You don't believe me? Companies like Facebook, Google or Amazon are among the most successful and most valuable companies in the world. Do you know why? Because they have a tremendous quantity and quality of data.
The value of data in the business world cannot be gainsaid, but it is only the prepared businesses can truly benefit from it. Your goal should be to embrace modern-day data management practices to generate quality insights from the data you collect. Work on building a culture that supports data analysis to enjoy the above benefit and more.
What makes a good growth hacker? A deep understanding and passionate curiosity are at the heart of what it takes to be successful in this role. They must understand how technology can contribute towards sustainable business-growth strategies while also knowing how customers think so that they know when adapting these plans will work best for them behaviorally as well! They don't do everything manually: a growth hacker has a lot of big data analysis tools in his toolkit to make his/her work better and automated.
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