How many times have you been on the receiving end of customer segmentation marketing that completely missed the mark? Just last week, I received a free sample of a plant-based cereal dubbed a superfood because…why, exactly? After all, I love my chocolate chip cookies as much as my green goddess salad. Another time, a targeted ad pushed an energy drink—you’d think, with an infant in the household, I would need an energy-inducing product; but what I’d rather have is a sleep aid. And recently an unsolicited catalog promoted matronly pantaloon pants and dusters covered in southwestern prints. Dare I ask: how old do you think I am, database?
No excuses for not being timely
With the influx of internal and external data, consumer products companies need to get targeted marketing right.
The message needs to be relevant at the right place and the right time. And timely offers need to reflect not just past purchasing behavior,
but also take into account life stage, life events, social trends, influencers, personality types, channel preference, product sentiment, assortments, affinities, tastes and so on.
By the microsecond, consumers are arming consumer product retailers with the information these companies need about them to make their pitches more receptive,
carry inventory with the right products at the right price, and grow their revenue across multiple channels.
Consumer segmentation and customer databases are no longer based on a few descriptive attributes that get left dormant over time.
The process is much more intricate and dynamic now, and more akin to a living organism.
Today, consumer product organizations can tap into data about consumers from a wealth of sources and data types that enable much more granular segmentation with persona-level attributing and with geospatial information.
And they can provide it at the hyper-local market level, factoring in social content—such as online reviews and tweets—along with weather information and local events to build effective promotions.A cognitive path to consumer insight
In your trade planning and promotional activities, consider a more consumer-centric approach.
A substantial number of promotions don’t break even, and spending on trade promotions by consumer product organizations accounts for a significant portion of gross sales.
What a waste—not to mention so many missed opportunities to keep consumers engaged and loyal to a brand.
Cognitive analytics enable consumer product companies to leverage valuable consumer and localized market insights to take the guesswork out of marketing.
They can create rich and highly dynamic consumer profiles, gauge sentiment and help improve demand forecasting and trade promotion plans with laser-like accuracy.
The other intrinsic benefit: they can shorten the go-to-market time for product launches, allowing marketers to adjust their strategy midcourse if needed.
Get more data-driven insight in this consumer products smart paper on how retailers and consumer products companies can learn from customer segmentation in an informative consumer products smart paper.
And that’s the thing. Some tool—or person—tasked with building my profile got it wrong, or at least wasn’t in sync with my life’s current state.
Being in sync is very important because what we intend to buy today will very likely not be the same as what we’ll want to purchase tomorrow, next week, next month or next year.
Recommendation engines are designed to help shoppers discover products they weren't searching for but would be inclined to buy.
Today, brick-and-mortar grocers are increasingly tapping the overarching technology behind recommendation engines: predictive analytics.
This type of analysis forecasts future trends based on present and past data, and it can help supermarkets boost business. A data-driven,
holistic evaluation of "buying triggers," such as seasonality, weather, inventory and promotions, is increasingly informing supermarkets' product mix, sales forecasts and marketing plans, according to a report from Express Analytics.
According to Progressive Grocer, supermarket Ahold USA used predictive analytics to guide its manufacturing and promotional strategies.
The company banked on the steady growth of pedometers due to an increased interest in fitness and the emergence of wearable technology.
Paul Scorza, CIO of the grocery chain, noted that the predictions to date had been very accurate.
Equipped with these data-driven tools, supermarkets can better identify what products shoppers want today and what they'll be searching for tomorrow,
and this knowledge will help them remain competitive for years to come. Connect with big data professionals via IBM's Consumer Products Industry Solutions Page to learn how.
By definition, groceries are a complex business, as food is perishable and storage logistics are complex. However, food is also a high-frequency purchase that's largely insulated from economic downturns.
As competition heats up in the grocery aisle, big data is gaining traction as the tool supermarkets need to counter rivals and remain profitable.To know more visit our site http://www.allindiayellowpage.com