Big data refers to data sets too large and complex for traditional data processing and data management applications. These large volumes of data can be both structured and unstructured, and it can inundate businesses on a daily basis. It can also include the vast amounts of valuable user data that marketing companies and campaigns can use to refine targeting and serve better offerings to a more specific audience.
Table of Contents:
- How to Use Publicly Accessible Data in Business Marketing
- Personalization in Digital Marketing
- Data Usage: Enhance Email Marketing Campaigns
- Types of Data to Use
- Knowing your Clientele
- Focus on Important data
- Fill in Data Holes
- Matching Existing Data with Customers
- 7 Ways Big Data is Changing the Face of Marketing
- Big Data & Advanced Analytics: Success Stories
- The Future of Big Data-Based Marketing
How to Use Publicly Accessible Data in Business Marketing
You can use public records to create customized marketing strategies and targeted ad delivery. Combining data such as demographics, personal preferences, and legal issues attached to buying profiles will highlight your target market.
This will give you an indicator of how best to advertise your products and services. Discovering what is important to your clients will help structure your marketing plan appropriately. Looking at US-based company Food Genius, they make use of open data to gain information on current trends in local restaurants to help companies such as the fast-food chain, Arby’s, market their products more intelligently.
Understanding the core mindset of your customers will ensure you target them specifically and more efficiently. You can then send out ads that zero in on their lifestyle choices, preferences, and desires.
The more you know your audience, the more apt they are to hear your message and take quick action. This will result in better sales conversion. It also opens the pathway for the promotion of increased revenue streams and repeat business. Satisfied customers will also refer others and come back for more.
Personalization in Digital Marketing
Website personalization is the practice of tailoring relevant or unique experiences to every visitor. The aim is to make customers feel special. Personalization is about creating a one-to-one marketing experience for customers. It begins with the collection of ample qualitative data about your audience.
To achieve this you must compile a detailed profile on each of your customers which you can do using a combination of email marketing and public records to create a comprehensive data set on your ideal client.
As a business, you may get overwhelmed by the massive influx of information you obtain and you might not know what to do with it. The best approach is to identify what you wish to obtain from the data and how it will fit your business needs. Proceed to find a few concentrated data streams, such as public records that provide the essential details, and use only those.
There is no need to over-saturate with data. It costs a lot to get data experts to mine information. A tighter focus results in the more efficient use of data collected. This is a quicker way to connect with your existing market research.
Data Usage: Enhance Email Marketing Campaigns
You can significantly enhance your email marketing campaigns through the harvested data of current subscribers. User data is key to sending relevant and timely emails through personalization, segmentation, and automation. The right data will help you attain email campaign success and higher conversion rates.
Types of Data to Use
1. Demographics – Collect basic A/S/L (age, sex, location) data. This can be obtained from subscribers when they sign up or make purchases. This type of data generally doesn’t change very often making it ideal for basic segmentation, personalization, and automated emails. You can then market very specific ranges of products and services like retirement planning for 30-40-year-olds, or cosmetic sales to female subscribers.
2. Preference – This type of data includes things like subscribers’ preferred products, services, brands, or desired frequency of mailing. Information is typically collected through a preference center. Preference data is dynamic and may change over time as the customer grows older. It’s therefore important to note that most people won’t update their preferences and then remind them to do so periodically.
3. Transactional – Review transactional data from your e-commerce platforms to ascertain purchase history. Importing this data into your email service provider may dramatically improve segmentation and personalization and opens up a whole new world for automated email marketing.
Transactional information allows you to identify who the most frequent customers are, who your highest value buyers are, and who hasn’t made a purchase yet. Examples of transactional data include; first and last purchase date, the total amount spent, number of purchases, average order value, and past products ordered.
4. Behavioral – Updated behavioral data is the most reliable indicator of what subscribers are interested in currently. This type of data is collected from an email (opens/clicks) or from a website (pages browsed/items carted). The most common type of behavioral email is a cart abandonment trigger.
This usually goes out within 24 hours of subscribers abandoning their cart. However, technology has advanced and there are new technologies available that allow you to follow up virtually on any action that a subscriber takes on a website. These may be used to send helpful, relevant emails based on the products, services, or topics they’ve recently browsed.
5. Segmentation – Using data, you can create highly targeted segments that combine demographics with preferences and transactional data. For example, you can target people of a particular demographic who are interested in a particular product category but who haven’t concluded an online purchase yet and offer them a first-purchase discount. Alternatively, you can target your customers who made high-value purchases in the last year and target them with a special VIP rewards offer.
6. Personalization – Research proves that personalized emails deliver six times higher transaction rates than non-personalized emails.
This requires data, easy-to-use personalization tools, and testing personalized email contents. With the right data tools, it can be very simple to implement. Examples of personalization may include addressing a customer by name, annual personalized birthday emails with discount offers, and product ads based on the subscriber’s brand and size preference.
Knowing your Clientele
Personalization delivers between five to eight times the return on investment (ROI) on marketing spend and can lift sales by 10% or more.
Unlock this by offering your customers personalized messages via email or text. It is important to track customers to understand their spending habits and offer them the best ideas for future purchases. You can track customers in multiple ways.
Most companies assign unique customer IDs linked to account details. However, they lack a systematic way to populate all the account’s data fields in order to form a comprehensive and holistic overview of the customer.
A systematic approach requires a business to identify and evaluate all customer interaction touchpoints. Avoid missing out on valuable insights by focusing on data that is already auto-populated in a customer account.
You can create applicable customer segments by looking at order fields like big spenders, loyal spenders, future spenders, and so on.A great example is found when looking at luxury fashion brand Burberry, and how they’ve used machine learning to create a deeper connection with their customers.
Focus on Important data
Pick out specific information for specific marketing goals. Key insights can be collected from transactional, browsing, and customer service data. This creates a rich set of consumer data profiles. This data is rarely all available in one place, but by using available email marketing and public records data you can combine all this information into a single management platform.
Fill in Data Holes
The following are the three main types of external data sources that are invaluable:
- Data you can buy – this includes broad consensus data, panel data, and travel cookie data.
- Data you can request from customers – this may be obtained through customer logins on a website.
- Data you can partner for – this usually happens between companies with complementing data sets combining insights through partnership.
Matching Existing Data with Customers
It’s possible to build complex algorithms based on your unique customer IDs. You will need an IT system that automatically updates a customer’s profile. This will update each time they interact with your business at a given touchpoint and scrub off old data to ensure accuracy. This tool is essential for businesses to stay up to date with what is on the actual ground.
7 Ways Big Data is Changing the Face of Marketing
1. Ad performance
Thanks to analytics, marketing budgets can be used more productively. This can be done by regularly testing, measuring campaigns often, and performing tweaks to get the best value out of each activity. Big data will determine which of your marketing options gets the best results. This is in regards to readership, likes, follows, shares, click-throughs, signups, and finalized transactions. You can stop spending money on ads that don’t work or that are reaching the wrong people and invest more of your budget in the areas which you can tell, statistically, will receive higher rates of return.
Big data is a building block in creating algorithms. Without ample data, algorithms are unable to learn. Big data orbits around the scale limit of human understanding. Artificial intelligence is required to reduce variables and conduct tasks too big and complex for the human mind. When you automate a process you increase marketing efficiency.
3. Customer Pricing
Over the years Big Data has helped marketers and businesses make better pricing decisions. Reports have proven that a 1% increase in price equates to an 8.7% increase in operating profits. This is done by making minute adjustments to prices, based on complex understandings of networks and behavioral economics.
For example, $9.99 will sell more as opposed to $10.00. Every invoice, email, or Twitter engagement will contain multiple pieces of data that can be used to develop pricing strategies.
4. Virtual Campaigns
Before Big Data could be harnessed marketers had to rely on different tools and tricks to gauge the success of their marketing campaigns. Today, Big Data has provided for campaign simulations where testing can be undertaken within a virtual marketplace. The result is that campaigns are more streamlined than in the past. Before the marketing campaign goes live, changes and tweaks can easily be put into place.
5. Small Business Big Tools
Recently, access to Big Data analysis has increased. The internet, through software, has made it possible to work with marketing teams from anywhere in the world. This has greatly reduced costs. The latest tools can be used to identify critical pieces of customer information. Converting marketing into a form of surveillance is getting easier by the day. It is easier to send multiple forms of adverts or custom offers simultaneously. This creates data points on a variety of factors that can be pulled apart by analysis.
6. Customer Segmentation Insight
Previously companies were left to create their own market data from which to create targeted ads. Today Big Data platforms are handing huge amounts of relevant data to marketers at lightning speed. The result? Specially curated adverts that are better targeted and more effective than ever before.
7. Customer Engagement and Loyalty
Big Data has had a real impact on the way that businesses interact with their current customers. It’s much cheaper to market to clients you’ve already won over once. It is also important to look for ways to get shoppers to buy from you repeatedly. This can be done by offering more personalization.
By checking the various data you have on your clients and how they shop, you can create more individual browsing and buying experiences. Tailor product suggestions and send them out. Use big data to help create the most suitable loyalty programs for clients and use this marketing strategy to its fullest extent.
Big Data & Advanced Analytics: Success Stories
Data has changed the lives of many. Raking in millions and billions for some. One of the most interesting data analytics success stories comes from Amazon. They were one of the early adopters of advanced analytics and are the only company that has a patent that allows them to ship goods before an order has even been placed.
The ‘customers who bought this…’ feature was revolutionary at the time. Today the bar has been set high. Now, data points are wide-ranging and far more specific to what a customer is likely to be genuinely interested in. The data points have a more rounded profile of a customer and are a great example of predictive analytics being used to its full potential.
How leading marketers turn insights into profits:
As with the example of Amazon above, marketers know that the best way to convert data into sales is by deciding on a definitive plan of action by following a certain sequence of steps:
- Identifying the business need that must be met, such as increased sales.
- Choosing the correct data that matches this need, like current customer base, and purchase history.
- Segmenting the data into usable information sets, like returning customers, high-value customers, non-purchasing customers.
- Setting up applicable campaigns to target those specific segments, like discounts per number of purchases for returning customers, VIP offers for high-value customers, and first-time purchase deals for new customers.
As more and more companies make use of big data analytics, you will see examples of how creative and endless the possibilities of data analytics really are. Take Coca Cola for instance, where product consistency is a major factor.
They made use of Big Data to identify over 600 possible flavors from orange crops used to produce their famous Minute Maid drink. Thereby eliminating variation in the final product whenever there were drops in crop availability and other sources would have to be used.
The Future of Big Data-Based Marketing
Due to the widespread accessibility of data and analytical tools, data-driven marketing is one of the hottest trends. Observation and measurement have always characterized data-driven marketing. Today, we can add to that insight-based analytics, and conversion statistics. In the future, the demand for consumer online behavioral data will only keep increasing and will be further refined.
The world of digital marketing is ever-changing and adapting. The current pandemic is a sober reminder of this fact. The Coronavirus has impacted consumer behavior. There’s been a spike in online sales and a drop in offline sales.
Businesses must shift their focus to how the pandemic is changing the landscape of consumer behavior and plan marketing tactics accordingly. This will mean placing less emphasis on brick and mortar stores, and more on creating a comprehensive online offering. Many have done this already with much success. The availability and optimum use of Big Data will be a game-changer for your business.