We present you the technology that uses artificial intelligence to analyze and discover brand new insights from your data, identifies problems and suggests solutions, and allows you to make important decisions much easier and faster.
Leading a successful and constantly growing business has always been a challenge. Navigating it through complex and turbulent times like these is even more challenging, so you need all the help you can get to continue winning customers. Investing in marketing has always been a safe way to secure revenue and growth, but with the budgets shrinking and the competition getting stronger, it is really tough to keep your eye on all moving parts affecting your company’s success.
Fortunately, here’s where technology can help. By utilizing the benefits of advanced tech solutions, led by artificial intelligence, business owners and marketers can see farther and make informed, data-driven decisions. But, with huge loads of data available from numerous platforms, they can sometimes get lost in the noise. Here is where augmented analytics comes to the rescue.
Using such advanced data assessment techniques to analyze past data and create projections, recommendations and alerts, brings a key competitive advantage in today’s fast-moving market. Companies and marketers that use advanced data analytics platforms which include augmented analytics features can act faster, invest wiser, and move way ahead of their competitors.
Area of application for augmented analytics is wide, so we have decided to focus on the industry we know best – marketing. This eBook will introduce you to augmented analytics, and take you through a set of practical examples that demonstrate how these advanced techniques can improve daily operations of marketers. Optimizing campaigns, reducing costs, preventing errors, anticipating market needs… these are just some of the advantages that augmented analytics can bring to marketers working in companies of all types and sizes.
Are you ready to get started? Great, let’s begin with the basics!
Augmented Analytics presents a practical use of a wide range of data processing techniques, such as data mining, statistical modelling and machine learning, engaged in analyzing a broad range of historical and current data in an attempt to enhance the way you can explore and analyze data. It achieves this by applying complex algorithms to the data, in order to model customer behavior, detect trends and anomalies, and make predictions that enable businesses to act based on insight, not instinct. In doing so, the technology ‘augments’ how businesses can use the data for further analysis in business intelligence apps.
In their overview of data analytics trends, one of world’s leading research and advisory companies Gartner explains the role of this technology in modern businesses: “Augmented analytics automates finding and surfacing the most important insights or changes in the business, to optimize decision making. It does this in a fraction of the time compared to manual approaches.” It is exactly this level of automation and process acceleration that is one of the key advantages of augmented analytics, as well as other technologies based on artificial intelligence.
You may not know this, but these technologies are already being used in various industries. Retailers use it to forecast inventory requirements or design store layouts for improved customer experience, airlines use it to set ticket prices, while hospitality firms use it to predict guest numbers. In fact, the augmented analytics market is predicted to grow at a compound annual rate of around 25% in the next five years, reaching a market size worth of 22.4 billion US Dollars by the year 2025. This level of growth shows the huge potential of these specialized analytics tools, and if you don’t start capitalizing it on time, chances are your competitors will very soon be one step ahead of you.
By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence.
- Rita Sallam, Distinguished Vice President Analyst, Gartner
Being a smart, flexible and powerful solution, augmented analytics presents a game changer for marketing practitioners, something they definitely need in a world where they need to achieve more with less. With this in mind, marketing analytics platforms that have an augmented analytics module are focused on proactively providing smart insights from marketing data, revealing valuable intelligence which could otherwise be missed or too time-consuming to obtain.
Augmented analytics enables marketers to make better informed, immediate decisions on their marketing activities by providing answers to the most critical questions, sometimes even before they emerge. And it allows them to optimize ongoing campaigns faster and more precisely, resolve potentially unseen issues before they become a massive problem, and ultimately maximize the ROI of all marketing activities.
For marketing, media and advertising agencies, augmented analytics presents a key tool in developing a strong competitive advantage. It allows them to cut through the enormous amounts of available data and quickly discover actionable insights. This will help them create additional value for clients, develop more effective strategies, and build and maintain the agency’s reputation.
And for corporate marketing practitioners, augmented analytics allows them to gain much greater and deeper insights than standard analytics tools and methods can provide. They can make data-driven decisions more quickly, based on emerging trends and monitored KPIs, maximizing campaign performance and ROI, and easily demonstrating the value they deliver to the business.
Augmented analytics brings marketing practitioners a wide range of benefits, and this eBook outlines four key areas where they can expect to gain massive advancements:
1. Maximizing ROI
2. Enhancing campaigns
3. Improving customer experience
4. Reinventing strategic directions
Along with businesses in general, marketing teams all around the world are dealing with frozen or shrinking budgets, but are still expected to build pipelines and grow the revenue. The good news is – with the benefits of augmented analytics, marketers no longer have to rely just on gut instinct, past experience, estimates, or trial and error.
Instead, they can rely on data-driven marketing decisions, based on insights created through augmented analytics. The technology behind it can provide an accurate picture of which campaigns are working and which aren’t, and help you achieve maximum returns on the budgets you allocate to each campaign. Here are three specific ways augmented analytics can help you optimize your marketing investments and allocate your budget effectively to get the best bang for your buck.
The beauty of augmented analytics lies in its ability to take data from multiple channels, such as Google Ads, Facebook, Shopify or any other platform, and apply powerful machine learning algorithms to uncover vital insights that can save money and improve the bottom line.
For example, a budget allocation feature can determine what mix of spend across various marketing channels will result in the maximum revenue for a given budget. It provides intelligence on this by learning about historical results and recent spend patterns, and creates a regression model for each channel to learn how spend on each of these has affected revenues over a longer period (going up to several years).
This functionality looks at the proportion between spend allocation and revenues over a certain period and across all channels, and compares this to what it has learned from the historical ROI figures. It then runs thousands of iterative calculations to determine the optimal budget spend for the upcoming period.
Another practical way augmented analytics can assist with operational improvements leading to greater marketing (and business) success is through Budget forecasting. Monitoring of spend versus allocated budget is notoriously time-consuming and prone to inaccuracies. Account managers in marketing and advertising agencies know this pain particularly well, as they need to monitor budgets of several clients at the same time.
To tackle this, the forecasting feature uses historical and current information to provide a true picture of your budget spend so far, and shows how it will continue if the campaign settings remain the same. Marketers can stay on track by acting on specific and timely suggestions for changes in spending, provided by the system. These suggestions also take into account typical seasonal variations, so if you keep a close eye on the information shown by this feature, there is little chance that the budget will be spent more quickly than planned.
Using this feature, agencies can ensure client budgets are correctly applied for each account, and each client is maximizing – but not exceeding – their budget. Brand campaign managers can ensure their allocated budgets are spent according to plan, and not overspent. And marketing managers can achieve a holistic view of actual spend versus budget, and focus on more granular analysis of over- and underspending to understand how to navigate future campaigns, and achieve higher levels of ROAS.
A third exciting area where augmented analytics can help marketers in their daily operations is Anomaly detection. This is where the tool uses historical data on metrics such as impressions, clicks or CPM, to self-learn and identify expectations for these metrics. If it detects an anomaly, such as an unexpected drop or spike, it will automatically flag the outlier.
The detected issue could be a mis-typed CPM value in an insertion order, which could quickly drain a budget without achieving the desired performance. Or, it might be incorrectly set product pricing values, leading to loss of revenue. An anomaly such as a sharp dip in ad impressions or conversions could indicate some type of technical issue on the ad platform or on your website, which should be corrected as soon as possible to minimize the negative effects.
"Errors can be costly"
If you make a typo and enter a daily budget value of $500 instead of $50.0 into Google Ads, in a month’s time your budget spend will reach $15,000 instead of the initially planned $1,500. Without any proactive analytics tech supporting you, this error could go unnoticed for weeks. But if you use an anomaly detection feature, you will get a notification in 24 hours or even less that something is wrong and you will save yourself (or your agency’s client) a lot of money and nerves.
These are often caused by tiny human errors, making them extremely difficult to identify and eliminate. Using the Anomaly detection feature in the Adverity platform, analysts can find ‘the needle in the haystack’ and get rid of it before it becomes a problem.
Anomaly detection gives marketers the chance to be one step ahead of any negative developments, helping them to optimize budgets and avoid campaign performance issues that might remain unnoticed until it’s too late and the budget is already spent.
Marketing is all about capturing the hearts, minds and ultimately the loyalty and wallets of customers. It’s a subtle and multilayered process based on identifying and engaging prospects, understanding their likes and needs, building relationships over time and leading them through a process that encourages them to actually becoming customers.
Marketing campaigns are the fundamental building blocks underpinning this process. Today’s digital marketing processes and technologies make it possible to run thousands of highly targeted campaigns simultaneously across the spectrum of ad platforms, eCommerce sites and social networks – from Google Ads and Bing Ads, through Amazon Marketplace, to Facebook, Instagram, or TikTok.
Augmented analytics is a powerful weapon for enhancing and tailoring campaigns. This is particularly important in a situation where you need to get it right the first time and achieve rapid results and growth with limited budgets and resources.
Marketers spend a lot of time getting their customer segmentation right – identifying the different target audiences they want to reach with content and messaging about their products and services. Augmented analytics takes this process even further, through automated and intelligent identification of segments that are performing well, such as specific geography, demographics, or technology used by the customer.
For example, Adverity’s Segment analysis feature enables marketers to get an even more granular view of the most effective segments emerging as their campaigns run. Then, they can refine or redefine their initial segment targeting, based on the insights learned as the campaign progresses. This helps them to sharpen the focus of their campaigns, so they reach the defined targets and achieve a higher conversion rate.
Segment analysis can also help marketers to identify the most appropriate channels for a certain campaign. For example, in a product campaign running in the Facebook network across multiple countries, it could be that the Instagram Stories in a particular country are especially effective, or have a lower cost for that type of a product, so it would be wise to shift available budget towards this channel for this product or segment.
When used in combination with a feature that helps with budget allocation, segment analysis enables marketing practitioners to allocate the right proportion of their budget to each channel, in order to achieve the highest ROAS.
Without this sort of deep insights, it would be very difficult to determine whether you should be spending more or less on each channel to get the best overall return for your budget. Using this sort of analysis means that marketers can now continually assess the performance of ad channels for each campaign, and fine tune both their ads and their budgets to get the best return on ad spend.
Last, but not least, augmented analytics can make campaigns more effective through trend detection. This functionality enables organizations to Identify emerging trends that can impact their business, such as market changes or activities from the competition. It saves time usually spent on manually researching trends and means that marketers will be able to proactively respond to constantly changing market conditions.
"Keep a close eye on the competition"
A slow, but steady increase in CPM values might go unnoticed for a while, so by the time you realize that your competitors are investing more or bidding against you aggressively, your budget might already be spent without any tangible results. With the Trend Detection feature, you will be able to notice this earlier and act accordingly
Adverity’s Trend detection feature works by collating historical data on a range of metrics, such as ad impressions, product sales or website visitors, intelligently normalizing them to allow for weekly and yearly seasonality, and eliminating any data noise. It then determines the overall trend across time, automatically creating charts and other data visualizations that show any significant trends that can have an effect on the marketing campaigns or the business as a whole.
This kind of a feature presents large benefit for marketers, because it is enabling them to identify decreasing or increasing trends for a specific product category, and act quickly to keep the accompanying campaign on track or enlarge it. In a similar way, agencies can automatically identify insightful trends for their clients, and save on hours trawling through data manually.
The pioneering retailers Harry Gordon Selfridge, John Wanamaker and Marshall Field coined a motto that was popularized in the 1800s: “The customer is always right”. While it’s still largely true, it’s also vital for businesses to make sure they attract the ‘right customers’ for them, and that they get to know them well.
Augmented analytics was not available to the likes of Selfridge, but it can provide today’s businesses with accurate and detailed information about their customers, insights they might have not been able to obtain through other analytics techniques. And since marketing is all about people, the greater insights you can glean, and the more you can understand the desires, activities and behavior of prospective customers, the more successful your marketing efforts will be.
Advanced analytics techniques enable companies to improve the customer experience, by developing a deep understanding of how customers interact with their brand through multiple channels. And, by unifying a diverse range of datasets, including website, CRM, demographic, psychographic and product usage data, it can provide marketing teams the detailed information they need to maximize customer value.
With this in mind, here are a few of ways on how advanced analytics can help you to improve your customer focus.
Analytics based on machine learning can be used to assist with sophisticated marketing practices, such as modeling and predicting customer behavior and calculating customer lifetime value. It achieves this by exploring large volumes of different types of information and running algorithms on multiple customer micro-segments to discover trends and patterns.
Customer micro-segmentation identifies the interests of specific groups by applying analytics techniques to customer information. It helps marketers to send targeted messaging and offers to these, now more precisely defined customer groups. By sending the right message at the right time to the right person(s), marketers significantly reduce the cost of customer acquisition, but also increase customer satisfaction, as they are no longer bombarded by irrelevant messages at inconvenient times.
You can establish micro-segments on a range of criteria, including geography, demographics (such as age, education and family unit), psychographic (personality type, lifestyle and values), and behavior (loyalty, buying patterns and price sensitivity). And by developing hundreds – or even thousands – of micro-segments, you can more accurately target your customers with the right mix of products, services and price points.
Banks identified new customer segments by using augmented analytics
Industry research done by Gartner has shown that banks were traditionally targeting older customers for wealth management services, under the assumption that this age group would be the most interested. Using augmented analytics, banks found out that clients aged 20 to 35 are actually more likely to transition into wealth management.
Marketing professionals can also use advanced analytics technology to improve customer retention and drive down churn. Tools based on artificial intelligence can be used to work out which customers are most likely to leave, for particular product or service combinations, in which specific segment, and at what point in the customer journey or lifetime.
This information can be used to trigger specific marketing interventions, for example, tailoring special offers or bundles to individuals to prevent churn, or winning back customers through appropriate messaging. Augmented analytics can advise you on the right marketing mix and tell you the best channel to reach targeted customers, whether that’s social media, email, SEM, TV, OOH or even a traditional mail campaign.
Companies in the telecommunications industry are known to be among the most advanced in handling vast amounts of data they have on their customers. By applying advanced analytics methodologies to this data and using specialized tools in analytics platforms such as Adverity, telcos are able to deliver highly customized and targeted information to perspective and existing customers, displaying the right offer to the right segment of customers.
Another great use of advanced analytics based on AI is product recommendation, which can also increase conversion rates and drive down customer churn. A product recommendation engine is a predictive analytics algorithm that digests all the available data on a customer prospect, and predicts which product, service or package they are likely to buy.
This may sound like science fiction, or something you don’t think is possible, but we have seen it in action, and it works. The algorithm carries out statistical analysis on as many data points as possible, on such things as customer demographics and psychographics, to get the most precise recommendation. You can combine this information with data from search queries and browsing habits to gain a more accurate picture of the prospect.
Then, based on a range of tested and proven product and service packages, and their adoption and churn rates for the prospect’s sub-category, the recommendation engine can suggest the best fit for each individual customer, optimizing cross-sell and upsell opportunities.
While augmented analytics can clearly transform marketing operations, as you have seen in all the examples listed above, it can also enable agencies and in-house marketing practitioners to bring strategic insights and innovation to clients and colleagues from other parts of the business. These insights can strengthen company-wide decision-making with timely and accurate data, and position marketing professionals as data-driven influencers in the organization, contributing significantly to the overall success.
The proactive insights and automation that augmented analytics brings can help to reduce risk, decrease manual effort, minimize the impact of issues, and quickly make performance improvements in marketing and other departments, based on the insights gained from this highly sophisticated ‘number crunching’. So, by tracking and analyzing diverse datasets, marketers can reduce costs, build pipeline, drive sales, and help retain customers.
Augmented analytics allows businesses to generate deeper insights than by using standard analytics tools and methods, which can give them a crucial competitive edge. It complements the set of business intelligence and analytics capabilities they already have, potentially uncovering issues and opportunities which may otherwise be missed. It can also be used to make unbiased suggestions for improvement, which is an important quality of artificial intelligence.
Marketers can therefore harness AI-based analytics to offer the business an unbiased, neutral view of business data, through features such as Trend Detection and Segment Analysis. These can deliver important information that is not influenced by personal opinion, feelings, likes, dislikes or experiences of marketers or business decision makers.
Likewise, for marketing agencies, augmented analytics cuts through the enormous amount of data available to them to quickly discover actionable insights for their clients, backed up by unbiased and neutral data points and trends. This allows an agency to act as an impartial third-party, and demonstrate that they can provide higher value to their clients. This in turn helps agencies to gain an important competitive advantage, build and maintain their reputation, and ultimately retain (even more satisfied) clients.
In addition, augmented analytics can help digital marketers to raise awareness in the business of new competition in the market. For example, identifying decreasing or increasing trends in ad metrics for a specific placement or campaign can provide powerful insights and competitive intelligence.
A player in a niche market will often encounter low CPM values, due to a lack of competition. However, spotting a trend of increasing CPM over time, for a campaign, country or channel, could indicate that new competitors have entered the market. By identifying this trend early, businesses can re-evaluate their go-to-market strategy and find new ways to combat the competitive threat before they lose market share.
Finally, marketing insights could be used to aid supply chain and inventory and stock management, and to streamline shipping. For example, with trend and anomaly detection or forecasting, it’s possible to track and anticipate factors such as order volumes, spikes in seasonal or regional demand, and shipping patterns.
A US-based fashion retailer recently used AI-based analytics technology to examine real-time data from its ERP and eCommerce platforms. The solution enabled store buyers, merchandisers and distribution channels to recognize in-demand products in real time, improve operational effectiveness and, ultimately, boost conversions and sales.
So, whether offering an unbiased view to the business, raising awareness of competitors, or facilitating smoother operations, augmented analytics can help marketing professionals to become important changemakers in their organizations.
