Marketing has evolved tremendously over the years, largely because technology has enabled it to reach, when the situation calls for it, either a bigger audience or a more specific, targeted audience. The Internet has helped businesses reach audiences at much faster speeds and lower costs than more traditional advertising methods.
Simply having a Web presence and using the right keywords will drive search engine users to a website. Unfortunately, this has a side effect: More brands than ever are competing for consumers' attention. That makes it even harder for businesses to ensure a memorable and impactful encounter with potential customers.
To that end, today's marketing departments face many challenges. Organisations are still identifying methods to make their products more customer- and market-driven, while businesses are pressured to drive more qualified leads to their sales teams and to work with product development to ensure they're delivering the products and services clients are asking for.
Addressing these issues requires a creative strategy and a platform that makes it easier to close the gap with the competition, increase brand awareness and reach customers at the right time.
Incorporate Big Data into marketing strategies
Some have identified marketing analytics as a way to resolve these challenges. A recent survey directed by Professor Christine Moorman and Sr. Professor of Business Administration T. Austin Finch with Duke University's Fuqua School of Business, found that marketing executives in the Fortune 1000 and Forbes 200 plan to increase their spending on marketing analytics in the next three years, some by as much as 60 percent. Many will be starting from scratch, as only 35 percent of respondents currently use marketing analytics.
Marketing analytics used in conjunction with big data will help many organisations properly evaluate their marketing performance, gain insight into their clients' purchasing habits, market trends and needs and make evidence-based marketing decisions. As one example, look at how politicians are using big data to identify their target audience and reach out to the so-called "silent majority."
With big data, there are several ways marketing executives can leverage existing data that's available internally, as well as external information received from a third-party vendor, in order to track the effectiveness of various marketing efforts.
These big data strategies include the following:
- Sentiment analysis
- Soft surveillance and consumer behavior tracking within retail stores
- Open communication channels with clients
- Predictive analytics (which can monitor inventory levels and ensure product availability)
- Analysis of customers' purchasing behaviours
- Response to value-added services based on clients' profiles and purchasing habits
- Effectiveness of real-time micro-segmentation of clientele targeted with custom tailored ads
Marketing departments should engage IT departments, and IT leadership, to help them accomplish these new goals. CIOs can then assist in creating a strategy that builds upon the data that's available internally. Such collaboration between forward-thinking CIOs and CMOs will become the basis of both competition and growth in organisations, as employees will look to use big data to find unique ways to outperform their competitors and peers.
It's safe to say that businesses of all sizes have access to platforms that in turn provide access to data and analysis.
While in some cases internal systems may not have all the transactional and historical data regarding operations, customer purchasing habits and marketing performance, many of today's systems do provide an easy, cost-effective way to get a head start on big data, as there are numerous open source big data technologies available for firms to use. For large data sets, there are several scalable pay-as-you-go services that can process and host data.
Different sectors, different uses for Big Data
The data that must be captured varies for marketing purposes. For online retailers, Web server logs, referring sources, page views, navigation patterns--basically all activities on the website--would be very beneficial. This lets retailers identify what keeps clients interested and what pushes them away.
For some retails, there's even the potential to mine a visitor's historical browsing patterns and searches and display items that she might have previously been interested, as well as similar items that wil likely interest her, when she returns to the site.
Brick-and-mortar retailers, on the other hand, face a different challenge. Loyalty cards have been, and remain, a popular method to capture shoppers' behavioral data. However, as stores increasingly offer free Internet to their customers, as well as mobile apps that provide electronic coupons, this provides data of great value to the retailer (not to mention a helpful service to the customer). Behind the scenes, the app gathers information that will help create a profile of the shopper. The app can also increase sales through the use of display ads.
In some cases, stores are implementing "soft surveillance" programs. Here a shopper who's not using a loyalty or reward card but who does use a retailer's mobile app is photographed as he or she walks through the main entrance. The customer can now be tracked throughout the store; the retailer can identify the sex, ethnicity and age of the shopper and, using that information, push customised ads to the mobile app.
The data that's collected can be used in a couple ways. The first model is a real-time response and feedback mechanism meant to influence a customer's purchases through video prompts related to his or her demographic information and based on observations made throughout his or her walk.
For example, a young man in workout clothes picking up a sports drink could be reminded that the store also sells vitamins designed specifically for high-energy sports enthusiasts, or someone picking up diabetic medication at the pharmacy could be pointed to healthy, low-sugar food choices. Identifying individual items that particular shoppers are likely to buy can impact the bottom line.
The second model requires a retailer to analyse all the data that's captured over time, identify patterns in how shoppers make purchasing decisions and determine what influenced their buying decisions.
For politicians, meanwhile, it is critical to connect and engage with voters. Having the ability to say the right thing to the right individuals and groups is a must if you seek votes.
As noted above, this year's election in the United States is making use of electronic data. Different people with different interests can visit the same candidate's website and see completely different messages and themes for them based on their visitor profiles.
Big data takes things a step further. Sites such as Klout can identify influencers real-time, allowing campaigns to target them with specific content to ensure so they can push the message downstream. In addition, real-time sentiment analysis during and after public speaking engagements lets PR machines educate candidates on what topics best connect them to voters, and what topics should be avoided, by monitoring both social media sites.
While in some cases it is far easier to focus on using data to increase market exposure and discover insight, it won't be uncommon to see firms using data they have collected from clients over the years to sell access and insight they have gained from their data.
For example, the data that manufacturers collect on faulty products can be sold, as it offers insight into how a component may behave under certain conditions. This information can easily provide a value-added service for a manufacturer, not to mention a new revenue stream.
Finally, telecommunication firms, free Wi-Fi providers and mobile carriers all retain information regarding customer's Web browsing habits. This information has tremendous value and can potentially be deidentified and sold--or, if the fine print states that information can be shared, then a consumer's information may be used and sold to telemarketers.
Big Data, big competitive advantage
The value that big data offers marketing executives, combined with the competition that drives businesses to seek market advantage, means we should expect to see increased investment in digital infrastructures.
As discussed, such technology can help retailers optimise and narrow the gap between what their clients want and what they actually receive. Financial services, healthcare and many other sectors will seek the opportunities and benefits that big data offers as well.
Reda Chouffani is a vice president at Biz Technology Solutions.
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